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156 rows where devstage_curation_coarse = "Undetermined" and tissue_curation = "Kidney"

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experiment.library_selection 3

technology 2

experiment.library_layout 2

tissue_curation_coarse 1

tissue_curation 1

  • Kidney · 156 ✖

experiment.platform 1

experiment.library_strategy 1

experiment.library_source 1

devstage_curation_coarse 1

  • Undetermined · 156 ✖

devstage_curation 1

Link rowid ▼ run.accession experiment.accession sample.accession study.accession bioproject study.title study.alias study.type study.abstract study.attributes study.PMIDs sample.description sample.title sample.alias sample.centername sample.attributes GEOsample.title GEOsample.dataprocessing GEOsample.source GEOsample.treatmentprotocol GEOsample.extractprotocol GEOsample.growthprotocol GEOsample.characteristics GEOsample.accession experiment.title experiment.alias experiment.library_name experiment.design_description experiment.library_construction_protocol experiment.attributes experiment.library_strategy experiment.library_source experiment.library_selection experiment.library_layout experiment.platform experiment.instrument_model experiment.spot_descriptor experiment.study_ref run.title run.attributes run.filename run.semantic_name run.total_bases run.total_spots run.alias run.read_lengths run.base_counts run.r1_length run.r2_length run.r3_length run.r4_length run.Acount run.Ccount run.Gcount run.Tcount run.Ncount run.experiment run.pool_member submission.accession submission.srasource submission.bioprojectsource seqdetective.n_mates seqdetective.mapping_rate.mate1 seqdetective.mapping_rate.mate2 seqdetective.nofeature_rate.mate1 seqdetective.nofeature_rate.mate2 seqdetective.sparsity.mate1 seqdetective.sparsity.mate2 seqdetective.pos_strand_rate.mate1 seqdetective.pos_strand_rate.mate2 seqdetective.readlen.mate1 seqdetective.readlen.mate2 seqdetective.judgement.mate1 seqdetective.judgement.mate2 seqdetective.judgement.reason platform_family instrument_generation read_bias selection_class prep_kit sc_or_bulk tech_class technology tech_variant submission.bioprojectsource.country earliest_date devstage_curation devstage_curation_coarse tissue_curation tissue_curation_coarse
11158 11158 ERR10047721 ERX9587609 ERS12570320 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Female 4 MF4 SAMEA110472297 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472297|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29737|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29737|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:372 85553 MF4 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EF12_1.fq.gz EF12_2.fq.gz fastq fastq 9295860000.0 30986200.0 ena RUN TAB 10 08 2022 10:54:39:372 85554 0:150 1:150 A:2456629138;C:2211534829;G:2202795083;T:2424808616;N:92334 150 150     2456629138 2211534829 2202795083 2424808616 92334 ERX9587609 ERS12570320 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.94791 0.94821 0.05293 0.05316 0.71285 0.71267 0.5054 0.50686 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11159 11159 ERR10047720 ERX9587608 ERS12570319 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Female 3 MF3 SAMEA110472296 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472296|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29736|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29736|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:372 85551 MF3 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EF11_1.fq.gz EF11_2.fq.gz fastq fastq 9515997600.0 31719992.0 ena RUN TAB 10 08 2022 10:54:39:372 85552 0:150 1:150 A:2541032543;C:2239204827;G:2227356932;T:2508310635;N:92663 150 150     2541032543 2239204827 2227356932 2508310635 92663 ERX9587608 ERS12570319 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95512 0.95547 0.06023 0.06014 0.70721 0.70658 0.51615 0.50766 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11160 11160 ERR10047719 ERX9587607 ERS12570318 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Female 2 MF2 SAMEA110472295 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472295|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29735|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29735|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:372 85549 MF2 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EF10_1.fq.gz EF10_2.fq.gz fastq fastq 10394476500.0 34648255.0 ena RUN TAB 10 08 2022 10:54:39:372 85550 0:150 1:150 A:2789547305;C:2438564969;G:2423744267;T:2742517499;N:102460 150 150     2789547305 2438564969 2423744267 2742517499 102460 ERX9587607 ERS12570318 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95582 0.95591 0.06231 0.06252 0.70565 0.70715 0.51407 0.51477 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11161 11161 ERR10047718 ERX9587606 ERS12570317 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Female 1 MF1 SAMEA110472294 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472294|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29734|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29734|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:372 85547 MF1 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EF9_1.fq.gz EF9_2.fq.gz fastq fastq 9531565200.0 31771884.0 ena RUN TAB 10 08 2022 10:54:39:372 85548 0:150 1:150 A:2534403521;C:2257857645;G:2242329348;T:2496889068;N:85618 150 150     2534403521 2257857645 2242329348 2496889068 85618 ERX9587606 ERS12570317 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95744 0.95773 0.05406 0.054 0.70703 0.70627 0.49691 0.49886 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11162 11162 ERR10047717 ERX9587605 ERS12570316 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Male 4 MM4 SAMEA110472293 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472293|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29733|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29733|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:371 85545 MM4 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EM16_1.fq.gz EM16_2.fq.gz fastq fastq 9801781200.0 32672604.0 ena RUN TAB 10 08 2022 10:54:39:371 85546 0:150 1:150 A:2617469644;C:2307347982;G:2294965646;T:2581792895;N:205033 150 150     2617469644 2307347982 2294965646 2581792895 205033 ERX9587605 ERS12570316 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95755 0.95764 0.0539 0.05338 0.71587 0.71484 0.51048 0.52067 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11163 11163 ERR10047716 ERX9587604 ERS12570315 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Male 3 MM3 SAMEA110472292 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472292|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29732|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29732|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:371 85543 MM3 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EM15_1.fq.gz EM15_2.fq.gz fastq fastq 9922431900.0 33074773.0 ena RUN TAB 10 08 2022 10:54:39:371 85544 0:150 1:150 A:2640289295;C:2345938205;G:2336699617;T:2599294368;N:210415 150 150     2640289295 2345938205 2336699617 2599294368 210415 ERX9587604 ERS12570315 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95894 0.95898 0.04903 0.04914 0.71346 0.71388 0.51462 0.51356 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11164 11164 ERR10047715 ERX9587603 ERS12570314 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Male 2 MM2 SAMEA110472291 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472291|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29731|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29731|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:371 85541 MM2 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EM14_1.fq.gz EM14_2.fq.gz fastq fastq 9470081700.0 31566939.0 ena RUN TAB 10 08 2022 10:54:39:371 85542 0:150 1:150 A:2518757590;C:2239498890;G:2227790286;T:2483847148;N:187786 150 150     2518757590 2239498890 2227790286 2483847148 187786 ERX9587603 ERS12570314 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95826 0.95753 0.05166 0.05151 0.71827 0.71725 0.50776 0.50874 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11165 11165 ERR10047714 ERX9587602 ERS12570313 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Mutant Male 1 MM1 SAMEA110472290 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472290|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29730|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29730|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:371 85539 MM1 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 EM13_1.fq.gz EM13_2.fq.gz fastq fastq 9896066100.0 32986887.0 ena RUN TAB 10 08 2022 10:54:39:371 85540 0:150 1:150 A:2615586694;C:2355549418;G:2345987621;T:2578734637;N:207730 150 150     2615586694 2355549418 2345987621 2578734637 207730 ERX9587602 ERS12570313 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.96075 0.9607 0.04898 0.04814 0.71914 0.71762 0.50604 0.51092 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11166 11166 ERR10047713 ERX9587601 ERS12570312 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Female 4 WF4 SAMEA110472289 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472289|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29729|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29729|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:370 85537 WF4 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WF4_1.fq.gz WF4_2.fq.gz fastq fastq 8902470600.0 29674902.0 ena RUN TAB 10 08 2022 10:54:39:370 85538 0:150 1:150 A:2387064218;C:2088721835;G:2083589487;T:2343005357;N:89703 150 150     2387064218 2088721835 2083589487 2343005357 89703 ERX9587601 ERS12570312 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95676 0.95666 0.0593 0.05927 0.70092 0.70337 0.49608 0.49899 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11167 11167 ERR10047712 ERX9587600 ERS12570311 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Female 3 WF3 SAMEA110472288 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472288|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29728|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29728|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:370 85535 WF3 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WF3_1.fq.gz WF3_2.fq.gz fastq fastq 9063103800.0 30210346.0 ena RUN TAB 10 08 2022 10:54:39:370 85536 0:150 1:150 A:2432312114;C:2123240631;G:2111227574;T:2396247669;N:75812 150 150     2432312114 2123240631 2111227574 2396247669 75812 ERX9587600 ERS12570311 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95482 0.95494 0.06998 0.07003 0.70122 0.70228 0.50936 0.50507 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11168 11168 ERR10047711 ERX9587599 ERS12570310 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Female 2 WF2 SAMEA110472287 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472287|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29727|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29727|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:370 85533 WF2 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WF2_1.fq.gz WF2_2.fq.gz fastq fastq 11904985800.0 39683286.0 ena RUN TAB 10 08 2022 10:54:39:370 85534 0:150 1:150 A:3185302826;C:2804829029;G:2783464897;T:3131272515;N:116533 150 150     3185302826 2804829029 2783464897 3131272515 116533 ERX9587599 ERS12570310 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95589 0.95646 0.058 0.05797 0.70457 0.70492 0.51464 0.5143 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11169 11169 ERR10047710 ERX9587598 ERS12570309 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Female 1 WF1 SAMEA110472286 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472286|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29726|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29726|sequencing method:Illumina NovaSeq 6000|sex:female|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:370 85531 WF1 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WF1_1.fq.gz WF1_2.fq.gz fastq fastq 9491977800.0 31639926.0 ena RUN TAB 10 08 2022 10:54:39:370 85532 0:150 1:150 A:2540140444;C:2236702404;G:2215435797;T:2499606420;N:92735 150 150     2540140444 2236702404 2215435797 2499606420 92735 ERX9587598 ERS12570309 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95868 0.95935 0.05681 0.05651 0.70487 0.70538 0.50749 0.50617 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11170 11170 ERR10047709 ERX9587597 ERS12570308 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Male 4 WM4 SAMEA110472285 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472285|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29725|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29725|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:369 85529 WM4 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WM8_1.fq.gz WM8_2.fq.gz fastq fastq 9911994300.0 33039981.0 ena RUN TAB 10 08 2022 10:54:39:369 85530 0:150 1:150 A:2647417182;C:2332033790;G:2324021308;T:2608423782;N:98238 150 150     2647417182 2332033790 2324021308 2608423782 98238 ERX9587597 ERS12570308 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95754 0.95758 0.05322 0.05309 0.71936 0.71898 0.52558 0.52697 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11171 11171 ERR10047708 ERX9587596 ERS12570307 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Male 3 WM3 SAMEA110472284 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472284|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29724|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29724|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:369 85527 WM3 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WM7_1.fq.gz WM7_2.fq.gz fastq fastq 10756015500.0 35853385.0 ena RUN TAB 10 08 2022 10:54:39:369 85528 0:150 1:150 A:2882486379;C:2526051573;G:2510570253;T:2836803943;N:103352 150 150     2882486379 2526051573 2510570253 2836803943 103352 ERX9587596 ERS12570307 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95343 0.9538 0.055 0.05491 0.71784 0.71883 0.53419 0.52955 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11172 11172 ERR10047707 ERX9587595 ERS12570306 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Male 2 WM2 SAMEA110472283 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472283|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29723|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29723|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:369 85525 WM2 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WM6_1.fq.gz WM6_2.fq.gz fastq fastq 8944434000.0 29814780.0 ena RUN TAB 10 08 2022 10:54:39:369 85526 0:150 1:150 A:2384550098;C:2112886362;G:2095147407;T:2351765069;N:85064 150 150     2384550098 2112886362 2095147407 2351765069 85064 ERX9587595 ERS12570306 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95717 0.95759 0.05527 0.05526 0.72009 0.72011 0.52634 0.52832 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
11173 11173 ERR10047706 ERX9587594 ERS12570305 ERP140136 PRJEB55250 Gene expression analysis in GLA mutant zebrafish revealed enhanced Ca2+ signaling similar to Fabry disease 0ed9a471-a4ab-4ec7-8113-a41cfa1601b4 Other Fabry disease is an X linked inborn metabolic disorder due to partial or complete deficiency of lysosomal a galactosidase A activity. The disease is characterized by progressive renal insufficiency with cardio and cerebrovascular involvement. The lack of experimental models of Fabry disease has limited the understanding of the disease and consequently has delayed the development of new therapies. Due to partial or complete deficiency of the lysosomal a galactosidase A activity the accumulation of glycosphingolipids is used as a marker. However recent studies suggested that they are not an ideal marker for treatment monitoring or treatment response. Here we use our GLA knockout zebrafish to investigate the possible biomarkers in an A4GALT free condition. We describe here an RNA sequencing analysis aiming to determine underlying transcriptomics signatures that could discriminate GLA mutant fish from the wild type fish in Gb3 free conditions. As in the FD we found an upregulated Ca2+ signaling pathway accompanied by downregulated cardiac muscle contraction pathway. In addition disrupted mitochondrial and lysosome related pathways in the mutant were observed and tested using immunohistochemistry. Our results point out that our model can mimic the effects of GLA mutations independently of the Gb 3 accumulation and potentially can be used to find new targets that improve FD outcomes. ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15   RNA seq Wild type Male 1 WM1 SAMEA110472282 Computational Biology Unit ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15|External Id:SAMEA110472282|INSDC center alias:Computational Biology Unit|INSDC center name:Computational Biology Unit|INSDC first public:2022 09 15T00:19:05Z|INSDC last update:2022 09 15T00:19:05Z|INSDC status:public|Submitter Id:ena SAMPLE TAB 08 08 2022 11:55:36:722 29722|collection date:2021 07|common name:zebrafish|sample name:ena SAMPLE TAB 08 08 2022 11:55:36:722 29722|sequencing method:Illumina NovaSeq 6000|sex:male|tissue type:Kidney                 Illumina NovaSeq 6000 paired end sequencing ena EXPERIMENT TAB 10 08 2022 10:54:39:368 85523 WM1 1     RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA Illumina NovaSeq 6000   ERP140136 Illumina NovaSeq 6000 paired end sequencing ENA FIRST PUBLIC:2022 09 15|ENA LAST UPDATE:2022 09 15 WM5_1.fq.gz WM5_2.fq.gz fastq fastq 9558564300.0 31861881.0 ena RUN TAB 10 08 2022 10:54:39:369 85524 0:150 1:150 A:2556941509;C:2249230277;G:2236855770;T:2515442411;N:94333 150 150     2556941509 2249230277 2236855770 2515442411 94333 ERX9587594 ERS12570305 ERA16825549 Computational Biology Unit|European Nucleotide Archive Computational Biology Unit 2 0.95505 0.95484 0.05372 0.05318 0.71798 0.71898 0.52584 0.52042 150 150 B B biological fallback assumption illumina novaseq_era unknown cdna_unspecified unknown bulk unknown unknown   Unknown 2022-09-15 Undetermined Undetermined Kidney Renal System
47861 47861 SRR6908751 SRX3856810 SRS3100403 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 unenriched GSM3070148   tissue:WKM9 unenriched|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM9 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070148 GSM3070148: WKM9 unenriched; Danio rerio; RNA Seq GSM3070148   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070148 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_unenriched_L001_R1_001.fastq.gz WKM9_unenriched_L001_R2_001.fastq.gz fastq fastq 1346805481.0 8925729.0 GSM3070148 r1 0:75.41 1:75.48 A:389424098;C:209314278;G:233588167;T:514471922;N:7016 75 75     389424098 209314278 233588167 514471922 7016 SRX3856810 SRS3100403 SRA675960 GEO Hubrecht Institute 2 0.43527 0.79133 0.35777 0.52091 0.95361 0.87156 0.48343 0.54164 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47862 47862 SRR6908752 SRX3856810 SRS3100403 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 unenriched GSM3070148   tissue:WKM9 unenriched|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM9 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070148 GSM3070148: WKM9 unenriched; Danio rerio; RNA Seq GSM3070148   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070148 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_unenriched_L002_R1_001.fastq.gz WKM9_unenriched_L002_R2_001.fastq.gz fastq fastq 1325332076.0 8783303.0 GSM3070148 r2 0:75.41 1:75.48 A:380077587;C:204687058;G:234896688;T:505666915;N:3828 75 75     380077587 204687058 234896688 505666915 3828 SRX3856810 SRS3100403 SRA675960 GEO Hubrecht Institute 2 0.42931 0.78191 0.35315 0.51028 0.95787 0.87493 0.49522 0.49685 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47863 47863 SRR6908753 SRX3856810 SRS3100403 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 unenriched GSM3070148   tissue:WKM9 unenriched|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM9 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070148 GSM3070148: WKM9 unenriched; Danio rerio; RNA Seq GSM3070148   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070148 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_unenriched_L003_R1_001.fastq.gz WKM9_unenriched_L003_R2_001.fastq.gz fastq fastq 1209174922.0 8013226.0 GSM3070148 r3 0:75.42 1:75.47 A:347525516;C:187142186;G:212384943;T:462099359;N:22918 75 75     347525516 187142186 212384943 462099359 22918 SRX3856810 SRS3100403 SRA675960 GEO Hubrecht Institute 2 0.4232 0.78709 0.34991 0.51583 0.9614 0.88215 0.50753 0.49857 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47864 47864 SRR6908754 SRX3856810 SRS3100403 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 unenriched GSM3070148   tissue:WKM9 unenriched|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM9 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070148 GSM3070148: WKM9 unenriched; Danio rerio; RNA Seq GSM3070148   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070148 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_unenriched_L004_R1_001.fastq.gz WKM9_unenriched_L004_R2_001.fastq.gz fastq fastq 1177710986.0 7804805.0 GSM3070148 r4 0:75.42 1:75.47 A:337640779;C:180611864;G:209653010;T:449785638;N:19695 75 75     337640779 180611864 209653010 449785638 19695 SRX3856810 SRS3100403 SRA675960 GEO Hubrecht Institute 2 0.42938 0.78452 0.35813 0.51351 0.96435 0.89035 0.46765 0.55409 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47865 47865 SRR6908747 SRX3856809 SRS3100401 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 monocytes GSM3070147   tissue:WKM9 monocytes|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM9 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070147 GSM3070147: WKM9 monocytes; Danio rerio; RNA Seq GSM3070147   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070147 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_monocytes_L001_R1_001.fastq.gz WKM9_monocytes_L001_R2_001.fastq.gz fastq fastq 1661471905.0 11011987.0 GSM3070147 r1 0:75.40 1:75.48 A:483808436;C:239092096;G:277634836;T:660929005;N:7532 75 75     483808436 239092096 277634836 660929005 7532 SRX3856809 SRS3100401 SRA675960 GEO Hubrecht Institute 2 0.36065 0.81129 0.26031 0.39596 0.96376 0.87584 0.46482 0.51218 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47866 47866 SRR6908748 SRX3856809 SRS3100401 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 monocytes GSM3070147   tissue:WKM9 monocytes|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM9 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070147 GSM3070147: WKM9 monocytes; Danio rerio; RNA Seq GSM3070147   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070147 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_monocytes_L002_R1_001.fastq.gz WKM9_monocytes_L002_R2_001.fastq.gz fastq fastq 1643858405.0 10895074.0 GSM3070147 r2 0:75.40 1:75.48 A:474610672;C:235181134;G:281183851;T:652878617;N:4131 75 75     474610672 235181134 281183851 652878617 4131 SRX3856809 SRS3100401 SRA675960 GEO Hubrecht Institute 2 0.35844 0.80892 0.26121 0.38966 0.96631 0.88008 0.45688 0.49263 74 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47867 47867 SRR6908749 SRX3856809 SRS3100401 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 monocytes GSM3070147   tissue:WKM9 monocytes|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM9 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070147 GSM3070147: WKM9 monocytes; Danio rerio; RNA Seq GSM3070147   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070147 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_monocytes_L003_R1_001.fastq.gz WKM9_monocytes_L003_R2_001.fastq.gz fastq fastq 1503593728.0 9965072.0 GSM3070147 r3 0:75.41 1:75.48 A:435191543;C:215315484;G:255248972;T:597807800;N:29929 75 75     435191543 215315484 255248972 597807800 29929 SRX3856809 SRS3100401 SRA675960 GEO Hubrecht Institute 2 0.3504 0.80674 0.25495 0.3888 0.96974 0.88402 0.4596 0.50684 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47868 47868 SRR6908750 SRX3856809 SRS3100401 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM9 monocytes GSM3070147   tissue:WKM9 monocytes|FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM9 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM9 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM9|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070147 GSM3070147: WKM9 monocytes; Danio rerio; RNA Seq GSM3070147   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070147 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM9_monocytes_L004_R1_001.fastq.gz WKM9_monocytes_L004_R2_001.fastq.gz fastq fastq 1474164037.0 9770113.0 GSM3070147 r4 0:75.41 1:75.48 A:425654229;C:209255453;G:253849148;T:585380972;N:24235 75 75     425654229 209255453 253849148 585380972 24235 SRX3856809 SRS3100401 SRA675960 GEO Hubrecht Institute 2 0.36215 0.81922 0.26584 0.39594 0.97096 0.89171 0.46223 0.51731 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47873 47873 SRR6908739 SRX3856807 SRS3100399 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 unenriched GSM3070145   tissue:WKM8 unenriched|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM8 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070145 GSM3070145: WKM8 unenriched; Danio rerio; RNA Seq GSM3070145   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070145 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_unenriched_L001_R1_001.fastq.gz WKM8_unenriched_L001_R2_001.fastq.gz fastq fastq 1667087336.0 11048469.0 GSM3070145 r1 0:75.40 1:75.49 A:475560256;C:240713376;G:276116899;T:674689422;N:7383 75 75     475560256 240713376 276116899 674689422 7383 SRX3856807 SRS3100399 SRA675960 GEO Hubrecht Institute 2 0.39157 0.8295 0.26694 0.3429 0.95806 0.85117 0.47471 0.5079 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47874 47874 SRR6908740 SRX3856807 SRS3100399 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 unenriched GSM3070145   tissue:WKM8 unenriched|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM8 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070145 GSM3070145: WKM8 unenriched; Danio rerio; RNA Seq GSM3070145   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070145 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_unenriched_L002_R1_001.fastq.gz WKM8_unenriched_L002_R2_001.fastq.gz fastq fastq 1643985440.0 10895186.0 GSM3070145 r2 0:75.40 1:75.49 A:465022994;C:236298663;G:278363355;T:664296206;N:4222 75 75     465022994 236298663 278363355 664296206 4222 SRX3856807 SRS3100399 SRA675960 GEO Hubrecht Institute 2 0.38307 0.82794 0.26079 0.33908 0.95966 0.85573 0.47886 0.53225 76 74 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47875 47875 SRR6908741 SRX3856807 SRS3100399 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 unenriched GSM3070145   tissue:WKM8 unenriched|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM8 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070145 GSM3070145: WKM8 unenriched; Danio rerio; RNA Seq GSM3070145   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070145 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_unenriched_L003_R1_001.fastq.gz WKM8_unenriched_L003_R2_001.fastq.gz fastq fastq 1497995831.0 9927192.0 GSM3070145 r3 0:75.41 1:75.48 A:423994108;C:216014805;G:251009522;T:606949772;N:27624 75 75     423994108 216014805 251009522 606949772 27624 SRX3856807 SRS3100399 SRA675960 GEO Hubrecht Institute 2 0.37662 0.82297 0.26009 0.33859 0.96382 0.8616 0.4713 0.53853 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47876 47876 SRR6908742 SRX3856807 SRS3100399 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 unenriched GSM3070145   tissue:WKM8 unenriched|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM8 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070145 GSM3070145: WKM8 unenriched; Danio rerio; RNA Seq GSM3070145   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070145 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_unenriched_L004_R1_001.fastq.gz WKM8_unenriched_L004_R2_001.fastq.gz fastq fastq 1462948321.0 9695189.0 GSM3070145 r4 0:75.41 1:75.48 A:413526172;C:209432303;G:247960945;T:592005236;N:23665 75 75     413526172 209432303 247960945 592005236 23665 SRX3856807 SRS3100399 SRA675960 GEO Hubrecht Institute 2 0.39195 0.83802 0.26623 0.34329 0.96301 0.86659 0.47028 0.53168 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47877 47877 SRR6908735 SRX3856806 SRS3100398 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 monocytes GSM3070144   tissue:WKM8 monocytes|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM8 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070144 GSM3070144: WKM8 monocytes; Danio rerio; RNA Seq GSM3070144   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070144 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_monocytes_L001_R1_001.fastq.gz WKM8_monocytes_L001_R2_001.fastq.gz fastq fastq 930630033.0 6164203.0 GSM3070144 r1 0:75.50 1:75.47 A:258982746;C:129522885;G:148763386;T:393303395;N:57621 75 75     258982746 129522885 148763386 393303395 57621 SRX3856806 SRS3100398 SRA675960 GEO Hubrecht Institute 2 0.32023 0.84288 0.2067 0.29948 0.98628 0.9247 0.4816 0.56903 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47878 47878 SRR6908736 SRX3856806 SRS3100398 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 monocytes GSM3070144   tissue:WKM8 monocytes|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM8 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070144 GSM3070144: WKM8 monocytes; Danio rerio; RNA Seq GSM3070144   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070144 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_monocytes_L002_R1_001.fastq.gz WKM8_monocytes_L002_R2_001.fastq.gz fastq fastq 840139689.0 5565664.0 GSM3070144 r2 0:75.50 1:75.45 A:236179715;C:116541374;G:133572472;T:353806731;N:39397 75 75     236179715 116541374 133572472 353806731 39397 SRX3856806 SRS3100398 SRA675960 GEO Hubrecht Institute 2 0.28608 0.81641 0.18643 0.30235 0.99159 0.94799 0.46036 0.51728 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47879 47879 SRR6908737 SRX3856806 SRS3100398 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 monocytes GSM3070144   tissue:WKM8 monocytes|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM8 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070144 GSM3070144: WKM8 monocytes; Danio rerio; RNA Seq GSM3070144   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070144 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_monocytes_L003_R2_001.fastq.gz WKM8_monocytes_L003_R1_001.fastq.gz fastq fastq 829094700.0 5491203.0 GSM3070144 r3 0:75.52 1:75.47 A:229473245;C:115123563;G:132541877;T:351944469;N:11546 75 75     229473245 115123563 132541877 351944469 11546 SRX3856806 SRS3100398 SRA675960 GEO Hubrecht Institute 2 0.27624 0.83541 0.18571 0.30162 0.99358 0.93693 0.46624 0.58337 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47880 47880 SRR6908738 SRX3856806 SRS3100398 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM8 monocytes GSM3070144   tissue:WKM8 monocytes|FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM8 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM8 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM8|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070144 GSM3070144: WKM8 monocytes; Danio rerio; RNA Seq GSM3070144   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070144 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM8_monocytes_L004_R1_001.fastq.gz WKM8_monocytes_L004_R2_001.fastq.gz fastq fastq 717316840.0 4751642.0 GSM3070144 r4 0:75.51 1:75.45 A:201002776;C:99055550;G:115888860;T:301362855;N:6799 75 75     201002776 99055550 115888860 301362855 6799 SRX3856806 SRS3100398 SRA675960 GEO Hubrecht Institute 2 0.24919 0.82101 0.16961 0.29185 0.99543 0.94882 0.43582 0.58134 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47885 47885 SRR6908727 SRX3856804 SRS3100396 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 unenriched GSM3070142   tissue:WKM7 unenriched|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM7 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070142 GSM3070142: WKM7 unenriched; Danio rerio; RNA Seq GSM3070142   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070142 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_unenriched_L001_R1_001.fastq.gz WKM7_unenriched_L001_R2_001.fastq.gz fastq fastq 1470115941.0 9738991.0 GSM3070142 r1 0:75.44 1:75.51 A:398948568;C:202294647;G:231760451;T:636827163;N:285112 75 75     398948568 202294647 231760451 636827163 285112 SRX3856804 SRS3100396 SRA675960 GEO Hubrecht Institute 2 0.40309 0.87046 0.32221 0.26166 0.99233 0.84327 0.29642 0.52123 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47886 47886 SRR6908728 SRX3856804 SRS3100396 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 unenriched GSM3070142   tissue:WKM7 unenriched|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM7 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070142 GSM3070142: WKM7 unenriched; Danio rerio; RNA Seq GSM3070142   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070142 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_unenriched_L002_R1_001.fastq.gz WKM7_unenriched_L002_R2_001.fastq.gz fastq fastq 1461695240.0 9683144.0 GSM3070142 r2 0:75.44 1:75.51 A:394008699;C:201030493;G:233919014;T:632480364;N:256670 75 75     394008699 201030493 233919014 632480364 256670 SRX3856804 SRS3100396 SRA675960 GEO Hubrecht Institute 2 0.38758 0.86795 0.30719 0.26558 0.99255 0.84607 0.30994 0.51718 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47887 47887 SRR6908729 SRX3856804 SRS3100396 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 unenriched GSM3070142   tissue:WKM7 unenriched|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM7 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070142 GSM3070142: WKM7 unenriched; Danio rerio; RNA Seq GSM3070142   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070142 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_unenriched_L003_R1_001.fastq.gz WKM7_unenriched_L003_R2_001.fastq.gz fastq fastq 1418045610.0 9393861.0 GSM3070142 r3 0:75.45 1:75.51 A:383399208;C:195487055;G:222663120;T:616484616;N:11611 75 75     383399208 195487055 222663120 616484616 11611 SRX3856804 SRS3100396 SRA675960 GEO Hubrecht Institute 2 0.41019 0.87176 0.32985 0.2642 0.99338 0.8452 0.2589 0.52225 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47888 47888 SRR6908730 SRX3856804 SRS3100396 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 unenriched GSM3070142   tissue:WKM7 unenriched|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM7 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070142 GSM3070142: WKM7 unenriched; Danio rerio; RNA Seq GSM3070142   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070142 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_unenriched_L004_R1_001.fastq.gz WKM7_unenriched_L004_R2_001.fastq.gz fastq fastq 1401330195.0 9283131.0 GSM3070142 r4 0:75.44 1:75.51 A:376049927;C:192808560;G:224900456;T:607563117;N:8135 75 75     376049927 192808560 224900456 607563117 8135 SRX3856804 SRS3100396 SRA675960 GEO Hubrecht Institute 2 0.40071 0.86588 0.31811 0.26185 0.99263 0.84569 0.27227 0.5224 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47889 47889 SRR6908723 SRX3856803 SRS3100395 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 monocytes GSM3070141   tissue:WKM7 monocytes|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM7 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070141 GSM3070141: WKM7 monocytes; Danio rerio; RNA Seq GSM3070141   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070141 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_monocytes_L001_R1_001.fastq.gz WKM7_monocytes_L001_R2_001.fastq.gz fastq fastq 1791125985.0 11864169.0 GSM3070141 r1 0:75.46 1:75.51 A:485867889;C:238293947;G:271424293;T:795194496;N:345360 75 75     485867889 238293947 271424293 795194496 345360 SRX3856803 SRS3100395 SRA675960 GEO Hubrecht Institute 2 0.42246 0.87038 0.34993 0.25475 0.99302 0.86906 0.3 0.50725 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47890 47890 SRR6908724 SRX3856803 SRS3100395 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 monocytes GSM3070141   tissue:WKM7 monocytes|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM7 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070141 GSM3070141: WKM7 monocytes; Danio rerio; RNA Seq GSM3070141   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070141 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_monocytes_L002_R1_001.fastq.gz WKM7_monocytes_L002_R2_001.fastq.gz fastq fastq 1792721494.0 11874637.0 GSM3070141 r2 0:75.46 1:75.51 A:482977185;C:238180503;G:276068534;T:795172908;N:322364 75 75     482977185 238180503 276068534 795172908 322364 SRX3856803 SRS3100395 SRA675960 GEO Hubrecht Institute 2 0.42187 0.86585 0.347 0.25727 0.99261 0.86983 0.32168 0.51044 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47891 47891 SRR6908725 SRX3856803 SRS3100395 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 monocytes GSM3070141   tissue:WKM7 monocytes|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM7 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070141 GSM3070141: WKM7 monocytes; Danio rerio; RNA Seq GSM3070141   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070141 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_monocytes_L003_R1_001.fastq.gz WKM7_monocytes_L003_R2_001.fastq.gz fastq fastq 1726273948.0 11434355.0 GSM3070141 r3 0:75.46 1:75.51 A:466721054;C:229970045;G:260445487;T:769123115;N:14247 75 75     466721054 229970045 260445487 769123115 14247 SRX3856803 SRS3100395 SRA675960 GEO Hubrecht Institute 2 0.43817 0.86963 0.36713 0.25464 0.99409 0.87136 0.28011 0.50765 75 73 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47892 47892 SRR6908726 SRX3856803 SRS3100395 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM7 monocytes GSM3070141   tissue:WKM7 monocytes|FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes WKM7 monocytes In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM7 monocytes   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM7|cell type:whole kidney marrow single cells|cell subtype:monocytes GSM3070141 GSM3070141: WKM7 monocytes; Danio rerio; RNA Seq GSM3070141   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070141 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM7_monocytes_L004_R1_001.fastq.gz WKM7_monocytes_L004_R2_001.fastq.gz fastq fastq 1706923699.0 11306267.0 GSM3070141 r4 0:75.46 1:75.51 A:458067525;C:226793433;G:263424046;T:758628361;N:10334 75 75     458067525 226793433 263424046 758628361 10334 SRX3856803 SRS3100395 SRA675960 GEO Hubrecht Institute 2 0.42414 0.86508 0.34964 0.25009 0.99375 0.87198 0.28225 0.51467 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47893 47893 SRR6908717 SRX3856802 SRS3100394 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM6 unenriched GSM3070140   tissue:WKM6 unenriched|FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM6 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM6 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070140 GSM3070140: WKM6 unenriched; Danio rerio; RNA Seq GSM3070140   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070140 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM6_unenriched_L001_R1_001.fastq.gz WKM6_unenriched_L001_R2_001.fastq.gz fastq fastq 1091182818.0 7228537.0 GSM3070140 r1 0:75.49 1:75.46 A:305460604;C:155608830;G:177642198;T:452400520;N:70666 75 75     305460604 155608830 177642198 452400520 70666 SRX3856802 SRS3100394 SRA675960 GEO Hubrecht Institute 2 0.32983 0.81725 0.21464 0.30328 0.98524 0.91348 0.47654 0.51388 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47894 47894 SRR6908718 SRX3856802 SRS3100394 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM6 unenriched GSM3070140   tissue:WKM6 unenriched|FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM6 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM6 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070140 GSM3070140: WKM6 unenriched; Danio rerio; RNA Seq GSM3070140   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070140 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM6_unenriched_L002_R1_001.fastq.gz WKM6_unenriched_L002_R2_001.fastq.gz fastq fastq 992904107.0 6578507.0 GSM3070140 r2 0:75.49 1:75.44 A:280993567;C:141013446;G:160470422;T:410379926;N:46746 75 75     280993567 141013446 160470422 410379926 46746 SRX3856802 SRS3100394 SRA675960 GEO Hubrecht Institute 2 0.3103 0.79506 0.20764 0.30662 0.99076 0.94178 0.49304 0.53389 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47895 47895 SRR6908720 SRX3856802 SRS3100394 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM6 unenriched GSM3070140   tissue:WKM6 unenriched|FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM6 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM6 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070140 GSM3070140: WKM6 unenriched; Danio rerio; RNA Seq GSM3070140   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070140 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM6_unenriched_L003_R1_001.fastq.gz WKM6_unenriched_L003_R2_001.fastq.gz fastq fastq 967648040.0 6409722.0 GSM3070140 r3 0:75.51 1:75.46 A:269841606;C:137530059;G:157502274;T:402760480;N:13621 75 75     269841606 137530059 157502274 402760480 13621 SRX3856802 SRS3100394 SRA675960 GEO Hubrecht Institute 2 0.304 0.80424 0.20488 0.29857 0.99383 0.92894 0.44008 0.5232 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47896 47896 SRR6908722 SRX3856802 SRS3100394 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM6 unenriched GSM3070140   tissue:WKM6 unenriched|FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM6 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM6 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM6|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070140 GSM3070140: WKM6 unenriched; Danio rerio; RNA Seq GSM3070140   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070140 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM6_unenriched_L004_R1_001.fastq.gz WKM6_unenriched_L004_R2_001.fastq.gz fastq fastq 843966623.0 5591352.0 GSM3070140 r4 0:75.50 1:75.44 A:238568640;C:119216971;G:138770810;T:347402234;N:7968 75 75     238568640 119216971 138770810 347402234 7968 SRX3856802 SRS3100394 SRA675960 GEO Hubrecht Institute 2 0.28014 0.78908 0.18667 0.29821 0.99496 0.94424 0.46594 0.52932 75 72 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47901 47901 SRR6908709 SRX3856800 SRS3100392 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 unenriched GSM3070138   tissue:WKM5 unenriched|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM5 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070138 GSM3070138: WKM5 unenriched; Danio rerio; RNA Seq GSM3070138   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070138 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_unenriched_L001_R1_001.fastq.gz WKM5_unenriched_L001_R2_001.fastq.gz fastq fastq 1616915014.0 10719306.0 GSM3070138 r1 0:75.41 1:75.43 A:470483106;C:225755405;G:263766190;T:656561040;N:349273 75 75     470483106 225755405 263766190 656561040 349273 SRX3856800 SRS3100392 SRA675960 GEO Hubrecht Institute 2 0.10729 0.72403 0.07307 0.20274 0.99017 0.84524 0.5068 0.51693 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47902 47902 SRR6908710 SRX3856800 SRS3100392 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 unenriched GSM3070138   tissue:WKM5 unenriched|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM5 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070138 GSM3070138: WKM5 unenriched; Danio rerio; RNA Seq GSM3070138   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070138 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_unenriched_L002_R1_001.fastq.gz WKM5_unenriched_L002_R2_001.fastq.gz fastq fastq 1573355252.0 10430670.0 GSM3070138 r2 0:75.40 1:75.44 A:458302389;C:217385315;G:261327273;T:636024406;N:315869 75 75     458302389 217385315 261327273 636024406 315869 SRX3856800 SRS3100392 SRA675960 GEO Hubrecht Institute 2 0.11064 0.71559 0.07574 0.19872 0.98981 0.85005 0.45203 0.52838 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47903 47903 SRR6908711 SRX3856800 SRS3100392 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 unenriched GSM3070138   tissue:WKM5 unenriched|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM5 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070138 GSM3070138: WKM5 unenriched; Danio rerio; RNA Seq GSM3070138   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070138 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_unenriched_L003_R2_001.fastq.gz WKM5_unenriched_L003_R1_001.fastq.gz fastq fastq 1566951274.0 10386628.0 GSM3070138 r3 0:75.42 1:75.44 A:451321309;C:220819392;G:256230144;T:638495895;N:84534 75 75     451321309 220819392 256230144 638495895 84534 SRX3856800 SRS3100392 SRA675960 GEO Hubrecht Institute 2 0.10189 0.72988 0.07219 0.20488 0.99281 0.83899 0.46012 0.51971 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47904 47904 SRR6908712 SRX3856800 SRS3100392 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 unenriched GSM3070138   tissue:WKM5 unenriched|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM5 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070138 GSM3070138: WKM5 unenriched; Danio rerio; RNA Seq GSM3070138   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070138 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_unenriched_L004_R1_001.fastq.gz WKM5_unenriched_L004_R2_001.fastq.gz fastq fastq 1470255063.0 9745929.0 GSM3070138 r4 0:75.41 1:75.45 A:425542718;C:206068561;G:242779977;T:595798063;N:65744 75 75     425542718 206068561 242779977 595798063 65744 SRX3856800 SRS3100392 SRA675960 GEO Hubrecht Institute 2 0.10318 0.71368 0.07165 0.20008 0.99159 0.8508 0.46642 0.51043 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47909 47909 SRR6908701 SRX3856798 SRS3100390 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 hspcs GSM3070136   tissue:WKM5 hspcs|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM5 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070136 GSM3070136: WKM5 hspcs; Danio rerio; RNA Seq GSM3070136   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070136 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_hspcs_L001_R2_001.fastq.gz WKM5_hspcs_L001_R1_001.fastq.gz fastq fastq 6064422368.0 40205564.0 GSM3070136 r1 0:75.42 1:75.41 A:1792101497;C:906329224;G:1061291018;T:2303411628;N:1289001 75 75     1792101497 906329224 1061291018 2303411628 1289001 SRX3856798 SRS3100390 SRA675960 GEO Hubrecht Institute 2 0.07707 0.61908 0.04536 0.14979 0.98711 0.86186 0.54256 0.52115 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47910 47910 SRR6908702 SRX3856798 SRS3100390 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 hspcs GSM3070136   tissue:WKM5 hspcs|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM5 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070136 GSM3070136: WKM5 hspcs; Danio rerio; RNA Seq GSM3070136   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070136 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_hspcs_L002_R1_001.fastq.gz WKM5_hspcs_L002_R2_001.fastq.gz fastq fastq 5921476240.0 39257421.0 GSM3070136 r2 0:75.41 1:75.43 A:1748991850;C:876000140;G:1055863619;T:2239402733;N:1217898 75 75     1748991850 876000140 1055863619 2239402733 1217898 SRX3856798 SRS3100390 SRA675960 GEO Hubrecht Institute 2 0.08014 0.61413 0.04634 0.14581 0.98654 0.8717 0.51292 0.50066 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47911 47911 SRR6908703 SRX3856798 SRS3100390 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 hspcs GSM3070136   tissue:WKM5 hspcs|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM5 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070136 GSM3070136: WKM5 hspcs; Danio rerio; RNA Seq GSM3070136   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070136 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_hspcs_L003_R1_001.fastq.gz WKM5_hspcs_L003_R2_001.fastq.gz fastq fastq 5866299339.0 38885339.0 GSM3070136 r3 0:75.43 1:75.43 A:1717556539;C:883848150;G:1028347614;T:2236229877;N:317159 75 75     1717556539 883848150 1028347614 2236229877 317159 SRX3856798 SRS3100390 SRA675960 GEO Hubrecht Institute 2 0.06878 0.62531 0.04189 0.15336 0.99113 0.85888 0.5 0.51754 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47912 47912 SRR6908704 SRX3856798 SRS3100390 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM5 hspcs GSM3070136   tissue:WKM5 hspcs|FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM5 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM5 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM5|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070136 GSM3070136: WKM5 hspcs; Danio rerio; RNA Seq GSM3070136   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070136 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM5_hspcs_L004_R1_001.fastq.gz WKM5_hspcs_L004_R2_001.fastq.gz fastq fastq 5566177327.0 36895726.0 GSM3070136 r4 0:75.42 1:75.44 A:1631791302;C:834536884;G:988788873;T:2110815191;N:245077 75 75     1631791302 834536884 988788873 2110815191 245077 SRX3856798 SRS3100390 SRA675960 GEO Hubrecht Institute 2 0.07494 0.61393 0.04705 0.14806 0.99032 0.87178 0.49704 0.51802 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47913 47913 SRR6908697 SRX3856797 SRS3100389 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM4 unenriched GSM3070135   tissue:WKM4 unenriched|FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM4 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM4 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070135 GSM3070135: WKM4 unenriched; Danio rerio; RNA Seq GSM3070135   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070135 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM4_unenriched_L001_R2_001.fastq.gz WKM4_unenriched_L001_R1_001.fastq.gz fastq fastq 1000182622.0 6625590.0 GSM3070135 r1 0:75.50 1:75.46 A:281062086;C:163533727;G:177503446;T:378045390;N:37973 75 75     281062086 163533727 177503446 378045390 37973 SRX3856797 SRS3100389 SRA675960 GEO Hubrecht Institute 2 0.32578 0.64735 0.27911 0.49563 0.94596 0.8396 0.51648 0.52037 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47914 47914 SRR6908698 SRX3856797 SRS3100389 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM4 unenriched GSM3070135   tissue:WKM4 unenriched|FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM4 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM4 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070135 GSM3070135: WKM4 unenriched; Danio rerio; RNA Seq GSM3070135   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070135 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM4_unenriched_L002_R2_001.fastq.gz WKM4_unenriched_L002_R1_001.fastq.gz fastq fastq 1024598143.0 6787724.0 GSM3070135 r2 0:75.49 1:75.46 A:287879816;C:166711858;G:184760618;T:385194933;N:50918 75 75     287879816 166711858 184760618 385194933 50918 SRX3856797 SRS3100389 SRA675960 GEO Hubrecht Institute 2 0.30906 0.63868 0.26505 0.49323 0.9498 0.84977 0.508 0.53041 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47915 47915 SRR6908699 SRX3856797 SRS3100389 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM4 unenriched GSM3070135   tissue:WKM4 unenriched|FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM4 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM4 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070135 GSM3070135: WKM4 unenriched; Danio rerio; RNA Seq GSM3070135   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070135 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM4_unenriched_L003_R2_001.fastq.gz WKM4_unenriched_L003_R1_001.fastq.gz fastq fastq 987354885.0 6540694.0 GSM3070135 r3 0:75.50 1:75.46 A:277978811;C:161185677;G:175345183;T:372839184;N:6030 75 75     277978811 161185677 175345183 372839184 6030 SRX3856797 SRS3100389 SRA675960 GEO Hubrecht Institute 2 0.32206 0.64379 0.27584 0.49734 0.94608 0.84764 0.51258 0.52761 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47916 47916 SRR6908700 SRX3856797 SRS3100389 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM4 unenriched GSM3070135   tissue:WKM4 unenriched|FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM4 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM4 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM4|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070135 GSM3070135: WKM4 unenriched; Danio rerio; RNA Seq GSM3070135   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070135 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM4_unenriched_L004_R1_001.fastq.gz WKM4_unenriched_L004_R2_001.fastq.gz fastq fastq 1001846281.0 6636299.0 GSM3070135 r4 0:75.50 1:75.46 A:280586899;C:163214034;G:180353077;T:377687027;N:5244 75 75     280586899 163214034 180353077 377687027 5244 SRX3856797 SRS3100389 SRA675960 GEO Hubrecht Institute 2 0.32088 0.64536 0.27364 0.4929 0.94663 0.84822 0.51406 0.53384 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47921 47921 SRR6908689 SRX3856795 SRS3100387 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM3 unenriched GSM3070133   tissue:WKM3 unenriched|FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM3 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM3 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070133 GSM3070133: WKM3 unenriched; Danio rerio; RNA Seq GSM3070133   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070133 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM3_unenriched_L001_R1_001.fastq.gz WKM3_unenriched_L001_R2_001.fastq.gz fastq fastq 1418323523.0 9398733.0 GSM3070133 r1 0:75.43 1:75.47 A:422643558;C:211337836;G:207870633;T:576229967;N:241529 75 75     422643558 211337836 207870633 576229967 241529 SRX3856795 SRS3100387 SRA675960 GEO Hubrecht Institute 2 0.38916 0.82774 0.31564 0.36709 0.96169 0.9177 0.50178 0.54487 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47922 47922 SRR6908690 SRX3856795 SRS3100387 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM3 unenriched GSM3070133   tissue:WKM3 unenriched|FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM3 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM3 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070133 GSM3070133: WKM3 unenriched; Danio rerio; RNA Seq GSM3070133   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070133 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM3_unenriched_L002_R1_001.fastq.gz WKM3_unenriched_L002_R2_001.fastq.gz fastq fastq 1297380885.0 8597567.0 GSM3070133 r2 0:75.43 1:75.47 A:384413707;C:192495936;G:194053875;T:526229304;N:188063 75 75     384413707 192495936 194053875 526229304 188063 SRX3856795 SRS3100387 SRA675960 GEO Hubrecht Institute 2 0.38661 0.82306 0.31693 0.35768 0.96171 0.92468 0.48342 0.54858 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47923 47923 SRR6908691 SRX3856795 SRS3100387 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM3 unenriched GSM3070133   tissue:WKM3 unenriched|FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM3 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM3 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070133 GSM3070133: WKM3 unenriched; Danio rerio; RNA Seq GSM3070133   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070133 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM3_unenriched_L003_R1_001.fastq.gz WKM3_unenriched_L003_R2_001.fastq.gz fastq fastq 1470091205.0 9741084.0 GSM3070133 r3 0:75.44 1:75.48 A:432738050;C:218429286;G:217928653;T:600846627;N:148589 75 75     432738050 218429286 217928653 600846627 148589 SRX3856795 SRS3100387 SRA675960 GEO Hubrecht Institute 2 0.39516 0.83773 0.32452 0.36027 0.96834 0.91662 0.49614 0.5268 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47924 47924 SRR6908692 SRX3856795 SRS3100387 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM3 unenriched GSM3070133   tissue:WKM3 unenriched|FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM3 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM3 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM3|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070133 GSM3070133: WKM3 unenriched; Danio rerio; RNA Seq GSM3070133   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070133 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM3_unenriched_L004_R1_001.fastq.gz WKM3_unenriched_L004_R2_001.fastq.gz fastq fastq 1400378972.0 9280367.0 GSM3070133 r4 0:75.43 1:75.46 A:412590948;C:206892406;G:210433218;T:570347127;N:115273 75 75     412590948 206892406 210433218 570347127 115273 SRX3856795 SRS3100387 SRA675960 GEO Hubrecht Institute 2 0.3812 0.82835 0.31027 0.35634 0.96889 0.93608 0.50533 0.53883 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47933 47933 SRR6908677 SRX3856791 SRS3100383 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM2 unenriched GSM3070130   tissue:WKM2 unenriched|FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM2 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070130 GSM3070130: WKM2 unenriched; Danio rerio; RNA Seq GSM3070130   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070130 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM2_unenriched_L001_R2_001.fastq.gz WKM2_unenriched_L001_R1_001.fastq.gz fastq fastq 1050338787.0 6957998.0 GSM3070130 r1 0:75.46 1:75.50 A:307962198;C:162998859;G:159301612;T:419897804;N:178314 75 75     307962198 162998859 159301612 419897804 178314 SRX3856791 SRS3100383 SRA675960 GEO Hubrecht Institute 2 0.40419 0.79829 0.34944 0.46358 0.95463 0.92715 0.5107 0.52123 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47934 47934 SRR6908678 SRX3856791 SRS3100383 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM2 unenriched GSM3070130   tissue:WKM2 unenriched|FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM2 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070130 GSM3070130: WKM2 unenriched; Danio rerio; RNA Seq GSM3070130   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070130 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM2_unenriched_L002_R1_001.fastq.gz WKM2_unenriched_L002_R2_001.fastq.gz fastq fastq 954172584.0 6321045.0 GSM3070130 r2 0:75.45 1:75.50 A:277724691;C:147647025;G:148192193;T:380472896;N:135779 75 75     277724691 147647025 148192193 380472896 135779 SRX3856791 SRS3100383 SRA675960 GEO Hubrecht Institute 2 0.40099 0.79668 0.34548 0.45475 0.95491 0.93168 0.512 0.51844 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47935 47935 SRR6908679 SRX3856791 SRS3100383 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM2 unenriched GSM3070130   tissue:WKM2 unenriched|FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM2 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070130 GSM3070130: WKM2 unenriched; Danio rerio; RNA Seq GSM3070130   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070130 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM2_unenriched_L003_R1_001.fastq.gz WKM2_unenriched_L003_R2_001.fastq.gz fastq fastq 1095988368.0 7259975.0 GSM3070130 r3 0:75.47 1:75.50 A:318145632;C:169141931;G:167581935;T:441001916;N:116954 75 75     318145632 169141931 167581935 441001916 116954 SRX3856791 SRS3100383 SRA675960 GEO Hubrecht Institute 2 0.4016 0.81167 0.34543 0.45854 0.96193 0.92427 0.51235 0.51464 76 74 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47936 47936 SRR6908680 SRX3856791 SRS3100383 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM2 unenriched GSM3070130   tissue:WKM2 unenriched|FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM2 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070130 GSM3070130: WKM2 unenriched; Danio rerio; RNA Seq GSM3070130   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070130 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM2_unenriched_L004_R1_001.fastq.gz WKM2_unenriched_L004_R2_001.fastq.gz fastq fastq 1028881429.0 6816251.0 GSM3070130 r4 0:75.46 1:75.49 A:298430122;C:158105868;G:160593676;T:411666228;N:85535 75 75     298430122 158105868 160593676 411666228 85535 SRX3856791 SRS3100383 SRA675960 GEO Hubrecht Institute 2 0.3924 0.79036 0.33854 0.45285 0.96386 0.94568 0.5146 0.50952 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47945 47945 SRR6908665 SRX3856788 SRS3100380 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM1 unenriched and eosinphils GSM3070127   tissue:WKM1 unenriched|FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM1 unenriched and eosinphils In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM1 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070127 GSM3070127: WKM1 unenriched and eosinphils; Danio rerio; RNA Seq GSM3070127   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070127 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM1_unenriched_and_eosinphils_L001_R1_001.fastq.gz WKM1_unenriched_and_eosinphils_L001_R2_001.fastq.gz fastq fastq 1068305818.0 7080529.0 GSM3070127 r1 0:75.40 1:75.48 A:320413848;C:151660462;G:160069867;T:435805461;N:356180 75 75     320413848 151660462 160069867 435805461 356180 SRX3856788 SRS3100380 SRA675960 GEO Hubrecht Institute 2 0.27598 0.80871 0.19091 0.22599 0.96861 0.84488 0.4721 0.52448 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47946 47946 SRR6908666 SRX3856788 SRS3100380 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM1 unenriched and eosinphils GSM3070127   tissue:WKM1 unenriched|FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM1 unenriched and eosinphils In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM1 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070127 GSM3070127: WKM1 unenriched and eosinphils; Danio rerio; RNA Seq GSM3070127   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070127 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM1_unenriched_and_eosinphils_L002_R1_001.fastq.gz WKM1_unenriched_and_eosinphils_L002_R2_001.fastq.gz fastq fastq 1016514463.0 6737139.0 GSM3070127 r2 0:75.40 1:75.49 A:302565774;C:144096988;G:155267617;T:414283021;N:301063 75 75     302565774 144096988 155267617 414283021 301063 SRX3856788 SRS3100380 SRA675960 GEO Hubrecht Institute 2 0.27295 0.81917 0.18669 0.22848 0.9668 0.84587 0.46708 0.53709 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47947 47947 SRR6908667 SRX3856788 SRS3100380 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM1 unenriched and eosinphils GSM3070127   tissue:WKM1 unenriched|FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM1 unenriched and eosinphils In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM1 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070127 GSM3070127: WKM1 unenriched and eosinphils; Danio rerio; RNA Seq GSM3070127   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070127 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM1_unenriched_and_eosinphils_L003_R1_001.fastq.gz WKM1_unenriched_and_eosinphils_L003_R2_001.fastq.gz fastq fastq 1086053144.0 7197705.0 GSM3070127 r3 0:75.40 1:75.48 A:318255993;C:154002465;G:165796480;T:447901015;N:97191 75 75     318255993 154002465 165796480 447901015 97191 SRX3856788 SRS3100380 SRA675960 GEO Hubrecht Institute 2 0.28052 0.80997 0.19564 0.22597 0.96765 0.84254 0.4696 0.52611 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47948 47948 SRR6908668 SRX3856788 SRS3100380 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM1 unenriched and eosinphils GSM3070127   tissue:WKM1 unenriched|FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM1 unenriched and eosinphils In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM1 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM1|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070127 GSM3070127: WKM1 unenriched and eosinphils; Danio rerio; RNA Seq GSM3070127   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070127 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM1_unenriched_and_eosinphils_L004_R1_001.fastq.gz WKM1_unenriched_and_eosinphils_L004_R2_001.fastq.gz fastq fastq 1085163813.0 7191653.0 GSM3070127 r4 0:75.40 1:75.49 A:312948861;C:153665711;G:169799718;T:448671627;N:77896 75 75     312948861 153665711 169799718 448671627 77896 SRX3856788 SRS3100380 SRA675960 GEO Hubrecht Institute 2 0.26916 0.8114 0.18523 0.22636 0.96627 0.84354 0.47209 0.51851 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47949 47949 SRR6908659 SRX3856787 SRS3100379 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 unenriched GSM3070126   tissue:WKM10 unenriched|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM10 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070126 GSM3070126: WKM10 unenriched; Danio rerio; RNA Seq GSM3070126   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070126 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_unenriched_L001_R1_001.fastq.gz WKM10_unenriched_L001_R2_001.fastq.gz fastq fastq 1891142652.0 12537041.0 GSM3070126 r1 0:75.42 1:75.42 A:557482402;C:271919044;G:315036968;T:746296246;N:407992 75 75     557482402 271919044 315036968 746296246 407992 SRX3856787 SRS3100379 SRA675960 GEO Hubrecht Institute 2 0.16858 0.70113 0.12017 0.25789 0.98484 0.84463 0.51282 0.51143 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47950 47950 SRR6908660 SRX3856787 SRS3100379 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 unenriched GSM3070126   tissue:WKM10 unenriched|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM10 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070126 GSM3070126: WKM10 unenriched; Danio rerio; RNA Seq GSM3070126   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070126 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_unenriched_L002_R1_001.fastq.gz WKM10_unenriched_L002_R2_001.fastq.gz fastq fastq 1846289680.0 12239657.0 GSM3070126 r2 0:75.41 1:75.43 A:544608247;C:262931581;G:312624132;T:725748545;N:377175 75 75     544608247 262931581 312624132 725748545 377175 SRX3856787 SRS3100379 SRA675960 GEO Hubrecht Institute 2 0.17135 0.69505 0.12425 0.25051 0.98466 0.85401 0.548 0.50623 76 74 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47951 47951 SRR6908662 SRX3856787 SRS3100379 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 unenriched GSM3070126   tissue:WKM10 unenriched|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM10 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070126 GSM3070126: WKM10 unenriched; Danio rerio; RNA Seq GSM3070126   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070126 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_unenriched_L003_R1_001.fastq.gz WKM10_unenriched_L003_R2_001.fastq.gz fastq fastq 1832938497.0 12149490.0 GSM3070126 r3 0:75.43 1:75.43 A:535224222;C:265875558;G:305945153;T:725790414;N:103150 75 75     535224222 265875558 305945153 725790414 103150 SRX3856787 SRS3100379 SRA675960 GEO Hubrecht Institute 2 0.14834 0.7084 0.1064 0.2628 0.98884 0.83997 0.47131 0.50686 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47952 47952 SRR6908663 SRX3856787 SRS3100379 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 unenriched GSM3070126   tissue:WKM10 unenriched|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched WKM10 unenriched In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070126 GSM3070126: WKM10 unenriched; Danio rerio; RNA Seq GSM3070126   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070126 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_unenriched_L004_R1_001.fastq.gz WKM10_unenriched_L004_R2_001.fastq.gz fastq fastq 1728520288.0 11457514.0 GSM3070126 r4 0:75.42 1:75.44 A:506773176;C:249233970;G:290907978;T:681531010;N:74154 75 75     506773176 249233970 290907978 681531010 74154 SRX3856787 SRS3100379 SRA675960 GEO Hubrecht Institute 2 0.15928 0.69759 0.11494 0.25416 0.98748 0.85257 0.49753 0.48714 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47957 47957 SRR6908651 SRX3856785 SRS3100378 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 hspcs GSM3070124   tissue:WKM10 hspcs|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM10 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070124 GSM3070124: WKM10 hspcs; Danio rerio; RNA Seq GSM3070124   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070124 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_hspcs_L001_R2_001.fastq.gz WKM10_hspcs_L001_R1_001.fastq.gz fastq fastq 1590301844.0 10544259.0 GSM3070124 r1 0:75.41 1:75.41 A:475941511;C:228957206;G:273207488;T:611864346;N:331293 75 75     475941511 228957206 273207488 611864346 331293 SRX3856785 SRS3100378 SRA675960 GEO Hubrecht Institute 2 0.1094 0.64845 0.07241 0.20022 0.99003 0.86858 0.47375 0.52521 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47958 47958 SRR6908652 SRX3856785 SRS3100378 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 hspcs GSM3070124   tissue:WKM10 hspcs|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM10 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070124 GSM3070124: WKM10 hspcs; Danio rerio; RNA Seq GSM3070124   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070124 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_hspcs_L002_R1_001.fastq.gz WKM10_hspcs_L002_R2_001.fastq.gz fastq fastq 1541424200.0 10220291.0 GSM3070124 r2 0:75.40 1:75.42 A:461686116;C:219412558;G:269584176;T:590440374;N:300976 75 75     461686116 219412558 269584176 590440374 300976 SRX3856785 SRS3100378 SRA675960 GEO Hubrecht Institute 2 0.10207 0.63661 0.06952 0.19781 0.9906 0.88067 0.49271 0.52658 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47959 47959 SRR6908653 SRX3856785 SRS3100378 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 hspcs GSM3070124   tissue:WKM10 hspcs|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM10 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070124 GSM3070124: WKM10 hspcs; Danio rerio; RNA Seq GSM3070124   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070124 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_hspcs_L003_R1_001.fastq.gz WKM10_hspcs_L003_R2_001.fastq.gz fastq fastq 1522328486.0 10091828.0 GSM3070124 r3 0:75.42 1:75.42 A:451216714;C:220917351;G:262800832;T:587312728;N:80861 75 75     451216714 220917351 262800832 587312728 80861 SRX3856785 SRS3100378 SRA675960 GEO Hubrecht Institute 2 0.13574 0.65823 0.09073 0.20336 0.99275 0.86434 0.43289 0.52956 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47960 47960 SRR6908654 SRX3856785 SRS3100378 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   WKM10 hspcs GSM3070124   tissue:WKM10 hspcs|FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs WKM10 hspcs In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode WKM10 hspcs   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:WKM10|cell type:whole kidney marrow single cells|cell subtype:hspcs GSM3070124 GSM3070124: WKM10 hspcs; Danio rerio; RNA Seq GSM3070124   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070124 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     WKM10_hspcs_L004_R1_001.fastq.gz WKM10_hspcs_L004_R2_001.fastq.gz fastq fastq 1411385405.0 9356766.0 GSM3070124 r4 0:75.41 1:75.43 A:420850958;C:203157222;G:246195731;T:541125854;N:55640 75 75     420850958 203157222 246195731 541125854 55640 SRX3856785 SRS3100378 SRA675960 GEO Hubrecht Institute 2 0.1075 0.63447 0.07148 0.19425 0.99168 0.87858 0.46045 0.52468 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47961 47961 SRR6908647 SRX3856784 SRS3100376 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched6 GSM3070123   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched6 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070123 GSM3070123: TD2 unenriched6; Danio rerio; RNA Seq GSM3070123   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070123 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched6_L001_R1_001.fastq.gz TD2_unenriched6_L001_R2_001.fastq.gz fastq fastq 545810961.0 3618641.0 GSM3070123 r1 0:75.34 1:75.49 A:168172042;C:76647486;G:75443312;T:225350562;N:197559 75 75     168172042 76647486 75443312 225350562 197559 SRX3856784 SRS3100376 SRA675960 GEO Hubrecht Institute 2 0.21696 0.7915 0.16188 0.2193 0.99671 0.95925 0.45419 0.56183 76 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47962 47962 SRR6908648 SRX3856784 SRS3100376 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched6 GSM3070123   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched6 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070123 GSM3070123: TD2 unenriched6; Danio rerio; RNA Seq GSM3070123   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070123 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched6_L002_R1_001.fastq.gz TD2_unenriched6_L002_R2_001.fastq.gz fastq fastq 551469212.0 3655214.0 GSM3070123 r2 0:75.36 1:75.52 A:164774688;C:77140941;G:80606976;T:228739873;N:206734 75 75     164774688 77140941 80606976 228739873 206734 SRX3856784 SRS3100376 SRA675960 GEO Hubrecht Institute 2 0.19654 0.81842 0.14863 0.22131 0.99734 0.94988 0.44495 0.52385 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47963 47963 SRR6908649 SRX3856784 SRS3100376 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched6 GSM3070123   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched6 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070123 GSM3070123: TD2 unenriched6; Danio rerio; RNA Seq GSM3070123   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070123 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched6_L003_R2_001.fastq.gz TD2_unenriched6_L003_R1_001.fastq.gz fastq fastq 450161969.0 2984169.0 GSM3070123 r3 0:75.35 1:75.50 A:138199135;C:62817422;G:62600807;T:186468898;N:75707 75 75     138199135 62817422 62600807 186468898 75707 SRX3856784 SRS3100376 SRA675960 GEO Hubrecht Institute 2 0.21607 0.79287 0.16404 0.21905 0.99703 0.95676 0.48017 0.55646 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47964 47964 SRR6908650 SRX3856784 SRS3100376 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched6 GSM3070123   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched6 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070123 GSM3070123: TD2 unenriched6; Danio rerio; RNA Seq GSM3070123   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070123 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched6_L004_R1_001.fastq.gz TD2_unenriched6_L004_R2_001.fastq.gz fastq fastq 442656356.0 2934612.0 GSM3070123 r4 0:75.33 1:75.51 A:135781084;C:61366386;G:62664738;T:182773713;N:70435 75 75     135781084 61366386 62664738 182773713 70435 SRX3856784 SRS3100376 SRA675960 GEO Hubrecht Institute 2 0.18178 0.75305 0.13685 0.21602 0.99776 0.9779 0.4152 0.56284 76 74 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47965 47965 SRR6908643 SRX3856783 SRS3100375 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched5 GSM3070122   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched5 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070122 GSM3070122: TD2 unenriched5; Danio rerio; RNA Seq GSM3070122   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070122 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched5_L001_R1_001.fastq.gz TD2_unenriched5_L001_R2_001.fastq.gz fastq fastq 693452896.0 4598401.0 GSM3070122 r1 0:75.33 1:75.48 A:213825079;C:97881059;G:95953069;T:285544984;N:248705 75 75     213825079 97881059 95953069 285544984 248705 SRX3856783 SRS3100375 SRA675960 GEO Hubrecht Institute 2 0.16673 0.76013 0.12371 0.17909 0.99671 0.95943 0.51028 0.50627 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47966 47966 SRR6908644 SRX3856783 SRS3100375 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched5 GSM3070122   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched5 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070122 GSM3070122: TD2 unenriched5; Danio rerio; RNA Seq GSM3070122   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070122 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched5_L002_R1_001.fastq.gz TD2_unenriched5_L002_R2_001.fastq.gz fastq fastq 699177190.0 4635107.0 GSM3070122 r2 0:75.34 1:75.50 A:208880260;C:98335526;G:102541505;T:289154313;N:265586 75 75     208880260 98335526 102541505 289154313 265586 SRX3856783 SRS3100375 SRA675960 GEO Hubrecht Institute 2 0.16993 0.79459 0.12771 0.18893 0.99693 0.94675 0.4163 0.53497 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47967 47967 SRR6908645 SRX3856783 SRS3100375 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched5 GSM3070122   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched5 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070122 GSM3070122: TD2 unenriched5; Danio rerio; RNA Seq GSM3070122   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070122 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched5_L003_R1_001.fastq.gz TD2_unenriched5_L003_R2_001.fastq.gz fastq fastq 576884372.0 3824943.0 GSM3070122 r3 0:75.33 1:75.49 A:177240215;C:80846391;G:80350870;T:238347702;N:99194 75 75     177240215 80846391 80350870 238347702 99194 SRX3856783 SRS3100375 SRA675960 GEO Hubrecht Institute 2 0.16558 0.7756 0.12819 0.17822 0.99709 0.95432 0.42857 0.53851 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47968 47968 SRR6908646 SRX3856783 SRS3100375 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched5 GSM3070122   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched5 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070122 GSM3070122: TD2 unenriched5; Danio rerio; RNA Seq GSM3070122   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070122 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched5_L004_R1_001.fastq.gz TD2_unenriched5_L004_R2_001.fastq.gz fastq fastq 576258135.0 3821008.0 GSM3070122 r4 0:75.32 1:75.49 A:176675655;C:80188796;G:82006998;T:237292671;N:94015 75 75     176675655 80188796 82006998 237292671 94015 SRX3856783 SRS3100375 SRA675960 GEO Hubrecht Institute 2 0.14911 0.72985 0.12068 0.18331 0.99831 0.97735 0.4031 0.53561 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47969 47969 SRR6908639 SRX3856782 SRS3100374 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched4 GSM3070121   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched4 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070121 GSM3070121: TD2 unenriched4; Danio rerio; RNA Seq GSM3070121   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070121 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched4_L001_R1_001.fastq.gz TD2_unenriched4_L001_R2_001.fastq.gz fastq fastq 698012656.0 4628160.0 GSM3070121 r1 0:75.33 1:75.49 A:215875472;C:99834912;G:97411477;T:284642018;N:248777 75 75     215875472 99834912 97411477 284642018 248777 SRX3856782 SRS3100374 SRA675960 GEO Hubrecht Institute 2 0.13242 0.78521 0.09514 0.21281 0.99695 0.96187 0.55958 0.54425 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47970 47970 SRR6908640 SRX3856782 SRS3100374 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched4 GSM3070121   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched4 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070121 GSM3070121: TD2 unenriched4; Danio rerio; RNA Seq GSM3070121   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070121 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched4_L002_R1_001.fastq.gz TD2_unenriched4_L002_R2_001.fastq.gz fastq fastq 700004319.0 4640053.0 GSM3070121 r2 0:75.35 1:75.52 A:209624561;C:99781032;G:103500007;T:286831762;N:266957 75 75     209624561 99781032 103500007 286831762 266957 SRX3856782 SRS3100374 SRA675960 GEO Hubrecht Institute 2 0.13829 0.81458 0.10266 0.21216 0.99687 0.94913 0.54395 0.53632 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47971 47971 SRR6908641 SRX3856782 SRS3100374 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched4 GSM3070121   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched4 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070121 GSM3070121: TD2 unenriched4; Danio rerio; RNA Seq GSM3070121   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070121 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched4_L003_R1_001.fastq.gz TD2_unenriched4_L003_R2_001.fastq.gz fastq fastq 574436722.0 3808300.0 GSM3070121 r3 0:75.34 1:75.50 A:177021417;C:81616991;G:80653244;T:235045589;N:99481 75 75     177021417 81616991 80653244 235045589 99481 SRX3856782 SRS3100374 SRA675960 GEO Hubrecht Institute 2 0.12255 0.79777 0.09509 0.21314 0.99772 0.95735 0.44927 0.54033 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47972 47972 SRR6908642 SRX3856782 SRS3100374 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched4 GSM3070121   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched4 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070121 GSM3070121: TD2 unenriched4; Danio rerio; RNA Seq GSM3070121   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070121 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched4_L004_R1_001.fastq.gz TD2_unenriched4_L004_R2_001.fastq.gz fastq fastq 569447738.0 3775476.0 GSM3070121 r4 0:75.32 1:75.51 A:175211390;C:80267913;G:81642398;T:232235494;N:90543 75 75     175211390 80267913 81642398 232235494 90543 SRX3856782 SRS3100374 SRA675960 GEO Hubrecht Institute 2 0.12315 0.75952 0.09398 0.20424 0.99784 0.97788 0.46825 0.56598 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47973 47973 SRR6908635 SRX3856781 SRS3100373 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched3 GSM3070120   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched3 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070120 GSM3070120: TD2 unenriched3; Danio rerio; RNA Seq GSM3070120   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070120 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched3_L001_R1_001.fastq.gz TD2_unenriched3_L001_R2_001.fastq.gz fastq fastq 1064615599.0 7058899.0 GSM3070120 r1 0:75.33 1:75.49 A:331155753;C:152195592;G:149457994;T:431416903;N:389357 75 75     331155753 152195592 149457994 431416903 389357 SRX3856781 SRS3100373 SRA675960 GEO Hubrecht Institute 2 0.12965 0.76924 0.09102 0.22546 0.99693 0.95895 0.46568 0.56174 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47974 47974 SRR6908636 SRX3856781 SRS3100373 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched3 GSM3070120   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched3 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070120 GSM3070120: TD2 unenriched3; Danio rerio; RNA Seq GSM3070120   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070120 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched3_L002_R1_001.fastq.gz TD2_unenriched3_L002_R2_001.fastq.gz fastq fastq 1070747888.0 7097567.0 GSM3070120 r2 0:75.35 1:75.51 A:322612282;C:152497154;G:159486633;T:435752070;N:399749 75 75     322612282 152497154 159486633 435752070 399749 SRX3856781 SRS3100373 SRA675960 GEO Hubrecht Institute 2 0.11805 0.79563 0.08703 0.22302 0.99738 0.94838 0.49404 0.53615 75 74 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47975 47975 SRR6908637 SRX3856781 SRS3100373 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched3 GSM3070120   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched3 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070120 GSM3070120: TD2 unenriched3; Danio rerio; RNA Seq GSM3070120   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070120 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched3_L003_R1_001.fastq.gz TD2_unenriched3_L003_R2_001.fastq.gz fastq fastq 886095506.0 5874463.0 GSM3070120 r3 0:75.34 1:75.50 A:274560800;C:125930642;G:125194660;T:360267888;N:141516 75 75     274560800 125930642 125194660 360267888 141516 SRX3856781 SRS3100373 SRA675960 GEO Hubrecht Institute 2 0.11795 0.77243 0.08536 0.2207 0.99752 0.95554 0.48447 0.53023 74 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47976 47976 SRR6908638 SRX3856781 SRS3100373 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched3 GSM3070120   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched3 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070120 GSM3070120: TD2 unenriched3; Danio rerio; RNA Seq GSM3070120   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070120 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched3_L004_R1_001.fastq.gz TD2_unenriched3_L004_R2_001.fastq.gz fastq fastq 886839338.0 5879735.0 GSM3070120 r4 0:75.33 1:75.50 A:274032562;C:125082235;G:128147333;T:359436665;N:140543 75 75     274032562 125082235 128147333 359436665 140543 SRX3856781 SRS3100373 SRA675960 GEO Hubrecht Institute 2 0.10406 0.73196 0.07637 0.22039 0.99805 0.97806 0.57024 0.5327 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47977 47977 SRR6908631 SRX3856780 SRS3100372 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched2 GSM3070119   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched2 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070119 GSM3070119: TD2 unenriched2; Danio rerio; RNA Seq GSM3070119   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070119 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched2_L001_R2_001.fastq.gz TD2_unenriched2_L001_R1_001.fastq.gz fastq fastq 704234076.0 4666720.0 GSM3070119 r1 0:75.40 1:75.51 A:214197936;C:98747742;G:99261324;T:291802858;N:224216 75 75     214197936 98747742 99261324 291802858 224216 SRX3856780 SRS3100372 SRA675960 GEO Hubrecht Institute 2 0.35492 0.86117 0.25299 0.26523 0.97461 0.90398 0.48193 0.51578 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47978 47978 SRR6908632 SRX3856780 SRS3100372 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched2 GSM3070119   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched2 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070119 GSM3070119: TD2 unenriched2; Danio rerio; RNA Seq GSM3070119   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070119 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched2_L002_R1_001.fastq.gz TD2_unenriched2_L002_R2_001.fastq.gz fastq fastq 765278281.0 5071250.0 GSM3070119 r2 0:75.39 1:75.51 A:229620635;C:106485326;G:110950848;T:318002131;N:219341 75 75     229620635 106485326 110950848 318002131 219341 SRX3856780 SRS3100372 SRA675960 GEO Hubrecht Institute 2 0.34672 0.85932 0.24701 0.26154 0.97309 0.90404 0.44868 0.53509 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47979 47979 SRR6908633 SRX3856780 SRS3100372 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched2 GSM3070119   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched2 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070119 GSM3070119: TD2 unenriched2; Danio rerio; RNA Seq GSM3070119   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070119 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched2_L003_R2_001.fastq.gz TD2_unenriched2_L003_R1_001.fastq.gz fastq fastq 687934305.0 4558488.0 GSM3070119 r3 0:75.41 1:75.51 A:206475938;C:96511863;G:97660355;T:287209767;N:76382 75 75     206475938 96511863 97660355 287209767 76382 SRX3856780 SRS3100372 SRA675960 GEO Hubrecht Institute 2 0.36436 0.861 0.2595 0.26448 0.97699 0.90772 0.47159 0.5237 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47980 47980 SRR6908634 SRX3856780 SRS3100372 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched2 GSM3070119   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched2 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070119 GSM3070119: TD2 unenriched2; Danio rerio; RNA Seq GSM3070119   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070119 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched2_L004_R2_001.fastq.gz TD2_unenriched2_L004_R1_001.fastq.gz fastq fastq 726529569.0 4814235.0 GSM3070119 r4 0:75.40 1:75.51 A:216493809;C:101292463;G:105024164;T:303652778;N:66355 75 75     216493809 101292463 105024164 303652778 66355 SRX3856780 SRS3100372 SRA675960 GEO Hubrecht Institute 2 0.35832 0.85478 0.25668 0.26566 0.97786 0.9232 0.43793 0.51027 75 74 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47981 47981 SRR6908627 SRX3856779 SRS3100371 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched1 GSM3070118   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched1 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070118 GSM3070118: TD2 unenriched1; Danio rerio; RNA Seq GSM3070118   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070118 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched1_L001_R1_001.fastq.gz TD2_unenriched1_L001_R2_001.fastq.gz fastq fastq 854990718.0 5665060.0 GSM3070118 r1 0:75.41 1:75.52 A:254734570;C:122614765;G:124439336;T:352929607;N:272440 75 75     254734570 122614765 124439336 352929607 272440 SRX3856779 SRS3100371 SRA675960 GEO Hubrecht Institute 2 0.36338 0.86281 0.26887 0.24825 0.97011 0.88966 0.52127 0.54178 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47982 47982 SRR6908628 SRX3856779 SRS3100371 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched1 GSM3070118   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched1 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070118 GSM3070118: TD2 unenriched1; Danio rerio; RNA Seq GSM3070118   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070118 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched1_L002_R1_001.fastq.gz TD2_unenriched1_L002_R2_001.fastq.gz fastq fastq 930416984.0 6164856.0 GSM3070118 r2 0:75.40 1:75.52 A:273371770;C:132477140;G:139134453;T:385153908;N:279713 75 75     273371770 132477140 139134453 385153908 279713 SRX3856779 SRS3100371 SRA675960 GEO Hubrecht Institute 2 0.35067 0.86515 0.25837 0.24485 0.97041 0.88838 0.50653 0.5351 76 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47983 47983 SRR6908629 SRX3856779 SRS3100371 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched1 GSM3070118   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched1 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070118 GSM3070118: TD2 unenriched1; Danio rerio; RNA Seq GSM3070118   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070118 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched1_L003_R1_001.fastq.gz TD2_unenriched1_L003_R2_001.fastq.gz fastq fastq 854585314.0 5662042.0 GSM3070118 r3 0:75.42 1:75.52 A:251015969;C:122655652;G:125410058;T:355402307;N:101328 75 75     251015969 122655652 125410058 355402307 101328 SRX3856779 SRS3100371 SRA675960 GEO Hubrecht Institute 2 0.37061 0.86557 0.27852 0.24591 0.97498 0.89335 0.49141 0.48962 75 75 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System
47984 47984 SRR6908630 SRX3856779 SRS3100371 SRP136633 PRJNA446034 Cell type purification by single cell transcriptome trained sorting GSE112438 Other Traditional cell type enrichment using fluorescence activated cell sorting FACS relies on methods that specifically label the cell type of interest. Here we propose GateID a computational method that combines single cell transcriptomics for unbiased cell type identification with FACS index sorting to purify cell types of choice. We validate GateID by purifying various cell types from the zebrafish kidney marrow and the human pancreas without xxx to specific antibodies or transgenes. Overall design: Single cell mRNA sequencing data of unenriched and enriched cells from zebrafish whole kidney marrow and human pancreas using GateID. For each cell we provide libraries with transcriptome information. An unenriched sample is transcriptome data from a live single cell FACS sort while an enriched library has transcriptome data for GateID enriched single cells for a given cell type.   pubmed:31585086   TD2 unenriched1 GSM3070118   tissue:TD2 unenriched|FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched TD2 unenriched1 In transcriptome libraries first read contains UMI 6 first nucleotides and cell barcode from 7 to 14 nucleotides and second reads contains biological information. Second reads with a valid cell barcode in corresponding first read are mapped to the reference transcriptome. Multimappers are not considered as valid. The cell specific barcode file is added as a part of processed data files. Genome build: All transcriptome libraries were mapped to Danio rerio assembly Zv9 ensemble 74 extended with ERCC92 Supplementary files format and content: Tabular separated files with transcript count rows per cell columns. Cells in each file are labeled according to barcode ID. The cell specific barcode file is provided in the celseq2 bc.csv.gz 1st column represents index of the cell specific barcode and the second column is the barcode TD2 unenriched   post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters   FISHid:TD2|cell type:whole kidney marrow single cells|cell subtype:unenriched GSM3070118 GSM3070118: TD2 unenriched1; Danio rerio; RNA Seq GSM3070118   1 post organ isolation live single cells are sorted into 384 well plates containing mineral oil uniquely barcoded cell specific primers for mRNA detection Spike in controls and and RNAse inhibitor. cellseq2 Illumina TruSeq adapaters GEO Accession:GSM3070118 RNA-Seq TRANSCRIPTOMIC cDNA PAIRED ILLUMINA NextSeq 500   SRP136633     TD2_unenriched1_L004_R1_001.fastq.gz TD2_unenriched1_L004_R2_001.fastq.gz fastq fastq 886769985.0 5875288.0 GSM3070118 r4 0:75.41 1:75.52 A:258347255;C:126714596;G:132415950;T:369203307;N:88877 75 75     258347255 126714596 132415950 369203307 88877 SRX3856779 SRS3100371 SRA675960 GEO Hubrecht Institute 2 0.36759 0.86048 0.27631 0.23985 0.97526 0.90682 0.49809 0.53286 75 76 T B mate1 technical by mapping diff illumina nextseq unknown random_priming trueseq sc single_cell_plate celseq   Netherlands 2018-03-28 Undetermined Undetermined Kidney Renal System

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CREATE TABLE run_metadata("run.accession" VARCHAR, "experiment.accession" VARCHAR, "sample.accession" VARCHAR, "study.accession" VARCHAR, bioproject VARCHAR, "study.title" VARCHAR, "study.alias" VARCHAR, "study.type" VARCHAR, "study.abstract" VARCHAR, "study.attributes" VARCHAR, "study.PMIDs" VARCHAR, "sample.description" VARCHAR, "sample.title" VARCHAR, "sample.alias" VARCHAR, "sample.centername" VARCHAR, "sample.attributes" VARCHAR, "GEOsample.title" VARCHAR, "GEOsample.dataprocessing" VARCHAR, "GEOsample.source" VARCHAR, "GEOsample.treatmentprotocol" VARCHAR, "GEOsample.extractprotocol" VARCHAR, "GEOsample.growthprotocol" VARCHAR, "GEOsample.characteristics" VARCHAR, "GEOsample.accession" VARCHAR, "experiment.title" VARCHAR, "experiment.alias" VARCHAR, "experiment.library_name" VARCHAR, "experiment.design_description" VARCHAR, "experiment.library_construction_protocol" VARCHAR, "experiment.attributes" VARCHAR, "experiment.library_strategy" VARCHAR, "experiment.library_source" VARCHAR, "experiment.library_selection" VARCHAR, "experiment.library_layout" VARCHAR, "experiment.platform" VARCHAR, "experiment.instrument_model" VARCHAR, "experiment.spot_descriptor" VARCHAR, "experiment.study_ref" VARCHAR, "run.title" VARCHAR, "run.attributes" VARCHAR, "run.filename" VARCHAR, "run.semantic_name" VARCHAR, "run.total_bases" DOUBLE, "run.total_spots" DOUBLE, "run.alias" VARCHAR, "run.read_lengths" VARCHAR, "run.base_counts" VARCHAR, "run.r1_length" BIGINT, "run.r2_length" BIGINT, "run.r3_length" BIGINT, "run.r4_length" BIGINT, "run.Acount" BIGINT, "run.Ccount" BIGINT, "run.Gcount" BIGINT, "run.Tcount" BIGINT, "run.Ncount" BIGINT, "run.experiment" VARCHAR, "run.pool_member" VARCHAR, "submission.accession" VARCHAR, "submission.srasource" VARCHAR, "submission.bioprojectsource" VARCHAR, "seqdetective.n_mates" BIGINT, "seqdetective.mapping_rate.mate1" DOUBLE, "seqdetective.mapping_rate.mate2" DOUBLE, "seqdetective.nofeature_rate.mate1" DOUBLE, "seqdetective.nofeature_rate.mate2" DOUBLE, "seqdetective.sparsity.mate1" DOUBLE, "seqdetective.sparsity.mate2" DOUBLE, "seqdetective.pos_strand_rate.mate1" DOUBLE, "seqdetective.pos_strand_rate.mate2" DOUBLE, "seqdetective.readlen.mate1" BIGINT, "seqdetective.readlen.mate2" BIGINT, "seqdetective.judgement.mate1" VARCHAR, "seqdetective.judgement.mate2" VARCHAR, "seqdetective.judgement.reason" VARCHAR, platform_family VARCHAR, instrument_generation VARCHAR, read_bias VARCHAR, selection_class VARCHAR, prep_kit VARCHAR, sc_or_bulk VARCHAR, tech_class VARCHAR, technology VARCHAR, tech_variant VARCHAR, "submission.bioprojectsource.country" VARCHAR, earliest_date DATE, devstage_curation VARCHAR, devstage_curation_coarse VARCHAR, tissue_curation VARCHAR, tissue_curation_coarse VARCHAR);;
CREATE INDEX idx_run_bioproject ON run_metadata(bioproject);;
CREATE INDEX idx_run_run_accession ON run_metadata("run.accession");;