{"database": "metadata", "table": "run_metadata", "is_view": false, "human_description_en": "where experiment.library_source = \"TRANSCRIPTOMIC\", technology = \"10x\" and tissue_curation = \"Pancreas\"", "rows": [[43988, "SRR6811827", "SRX3768867", "SRS3023384", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Pancreas 3 endo scar", "GSM3032170", null, "source name:Primary pancreatic islet|strain/background:Zebrabow M|tissue:Primary pancreatic islet|developmental stage:Adult", "Pancreas 3 endo scar", "Library strategy: Targeted amplification Scar reads have the same structure as transcript reads: they consist of a barcode  a UMI and a scar. The scar sequences were aligned using bwa mem6 to a reference of RFP. We defined a cell as a barcode with at least 500 reads. We removed reads that were unmapped  had an incorrect barcode  or did not start with the exact PCR primer we used. We truncated all scar sequences to 75 nucleotides and filtered out shorter sequences. To correct for sequencing errors  we implemented several rounds of scar filtering Supplementary Fig. 2 in publication. We started by counting the number of times each molecule was sequenced. Sequencing errors will typically have fewer reads than the actual scars they originate from. As a first filtering step  we therefore removed all molecules only seen once to reduce the complexity in the dataset for consecutive filtering steps. In the second filtering step  we aimed to remove easily recognizable sequencing errors. To this end  we consecutively considered scar sequences that have the same cellular barcode and UMI  UMIs that have the same cellular barcode and scar sequence  and cellular barcodes that have the same UMI and scar sequence. In each step  we kept only the molecule with the highest number of reads. The rationale behind this is that it is very improbable to have two valid scar sequences in the same cell with the same UMI  or to have a scar sequence with the same UMI appear in two different cells. The observation of two different UMIs for the same scar in the same cell is much more likely and corresponds to detection of multiple transcripts from the same locus  but information about scar expression levels was not required in our downstream analysis. In the third filtering step  we specifically targeted sequencing errors within each cell. We compared the scar sequences found within a cell to each other. We filtered out sequences that had a Hamming distance of 2 or less to another scar sequence in the same cell that occurred in at least eight times as many reads. Scar sequences in the same cell that were one Hamming distance apart but had a read ratio less than eight were tested on three criteria if both of them occurred at least twice in the scar library: Do both scars have more than one transcript?  Do both scars occur in cells independently from each other?  Do the UMIs of both scars have Hamming distance of two or more? If two of these criteria were true  the scars were kept and the sequences were placed on a list of validated scars that  if they occurred in the same cell in another library  did not have to be tested anymore. If one or zero criteria were true  the scar that had only one transcript  or the scar that did not occur independently  were filtered out. Genome build: N/A Supplementary files format and content: List of scar transcripts with cell barcode  scar name  cell type  scar probability and number of organisms that have this cell.", "Primary pancreatic islet", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Primary pancreatic islet|developmental stage:Adult", "GSM3032170", "GSM3032170: Pancreas 3 endo scar; Danio rerio; OTHER", "GSM3032170", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032170", "OTHER", "TRANSCRIPTOMIC", "other", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "P7endo_scar_R1.fastq.gz P7endo_scar_R2.fastq.gz", "fastq fastq", 2537781396.0, 20465979.0, "GSM3032170 r1", "0:26 1:98", "A:741745261;C:801599713;G:561531527;T:431666561;N:1238334", 26, 98, null, null, 741745261, 801599713, 561531527, 431666561, 1238334, "SRX3768867", "SRS3023384", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00014, 0.00289, 0.00012, 0.00028, 0.99995, 0.99602, 1.0, 0.68478, 26, 98, "T", "T", "mates < 9% mapping rate", "illumina", "nextseq", "unknown", "other", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Adult", "Adult", "Pancreas", "Endocrine System"], [43994, "SRR6811821", "SRX3768861", "SRS3023378", "SRP121343", "PRJNA415636", "Simultaneous lineage tracing and cell type identification using CRISPR/Cas9 induced genetic scars", "GSE106121", "Other", "A key goal of developmental biology is to understand how a single cell transforms into a full grown organism consisting of many different cell types. Single cell RNA sequencing scRNA seq has become a widely used method due to its ability to identify all cell types in a tissue or organ in a systematic manner. However  a major challenge is to organize the resulting taxonomy of cell types into lineage trees revealing the developmental origin of cells. Here  we present a strategy for simultaneous lineage tracing and transcriptome profiling in thousands of single cells. By combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes  we reconstruct developmental lineage trees in zebrafish larvae and adult fish. In future analyses  LINNAEUS LINeage tracing by Nuclease Activated Editing of Ubiquitous Sequences can be used as a systematic approach for identifying the lineage origin of novel cell types  or of known cell types under different conditions. Overall design: Combining scRNA seq with computational analysis of lineage barcodes generated by genome editing of transgenic reporter genes.", null, "pubmed:29644996", null, "Pancreas 3 endo mRNA", "GSM3032164", null, "source name:Primary pancreatic islet|strain/background:Zebrabow M|tissue:Primary pancreatic islet|developmental stage:Adult", "Pancreas 3 endo mRNA", "Alignment and transcript counting of libraries were done using Cell Ranger 2.0.2. Cell numbers to be extracted were set at a minimum of 6000 but were increased if there were substantially more cells with more than 500 unique transcripts. Exact numbers can be found in Supplementary Table 1 of publication. Genome build: GRCz10   release 90 Supplementary files format and content: * matrix.mtx: Single cell transcript count table; * barcodes.tsv: List of cell barcodes.", "Primary pancreatic islet", null, "Single cell dissociation. 10X Genomics Chromium", null, "strain/background:Zebrabow M|tissue:Primary pancreatic islet|developmental stage:Adult", "GSM3032164", "GSM3032164: Pancreas 3 endo mRNA; Danio rerio; RNA Seq", "GSM3032164", null, "1", "Single cell dissociation. 10X Genomics Chromium", "GEO Accession:GSM3032164", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP121343", null, null, "P7endo_wt_R1.fastq.gz P7endo_wt_R2.fastq.gz", "fastq fastq", 41593781900.0, 335433725.0, "GSM3032164 r1", "0:26 1:98", "A:11833690021;C:9547054378;G:9724089290;T:10470148302;N:18799909", 26, 98, null, null, 11833690021, 9547054378, 9724089290, 10470148302, 18799909, "SRX3768861", "SRS3023378", "SRA623333", "GEO", "Max Delbr\u00fcck Center", 2, 0.00308, 0.92936, 0.00192, 0.05695, 0.9973, 0.8686, 0.45945, 0.58814, 26, 98, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2018-03-06", "Adult", "Adult", "Pancreas", "Endocrine System"], [50847, "SRR8312900", "SRX5126276", "SRS4139398", "SRP173304", "PRJNA509469", "Single cell RNA sequencing of zebrafish pancreatic cells", "GSE123662", "Other", "The pancreatic beta cells regulate blood glucose levels by secreting the hormone insulin in response to increasing glucose levels. Recent work has identified molecular and functional heterogeneity among the beta cell community. To ontain an unbiased picture into the molecular heterogeneity present in zebrafish pancreatic cells  we performed droplet based next generation sequencing of individual pancreatic cells. Using unsupervised clustering  we could identify all the major cell types present in the pancreas. Moreover  we could define sub populations within the major cell types  demonstrating the presence of molecular heterogeneity within nominally homogenous cell populations. Overall design: We used 10x Genomics to profile pancreatic cells from zebrafish. Pancreatic islets from six animals were dissociated and single cell library prepared using 10x Genomics Chromium pipeline. Sequencing was performed on llumina NextSeq 550 machine using a HighOutput flowcell in paired end mode R1: 26 cycles; I1: 8 cycles; R2: 57 cycles  thus generating 45 mio fragments. The raw sequencing data was then processed with the 'count' command of the Cell Ranger software v2.1.0 provided by 10X Genomics with the option '  expect cells' set to 5000 all other options were used as per default. To build the reference for Cell Ranger  zebrafish genome GRCz10 as well as gene annotation Ensembl 87 were downloaded from Ensembl and the annotation was filtered with the 'mkgtf' command of Cell Ranger options: '  attribute=gene biotype:protein coding   attribute=gene biotype:lincRNA \u2013attribute=gene biotype:antisense'. Genome sequence and filtered annotation were then used as input to the 'mkref' command of Cell Ranger to build the appropriate Cellranger Reference.", null, "pubmed:32694805", null, "2mpf Pancreas", "GSM3509161", null, "tissue:pancreatic cells|age:2mpf|strain:Tgins:BB1.0L|disease state:Normal", "2mpf Pancreas", "The raw sequencing data was then processed with the \u2018count\u2019 command of the Cell Ranger software v2.1.0 provided by 10X Genomics with the option \u2018  expect cells\u2019 set to 5000 all other options were used as per default. To build the reference for Cell Ranger  zebrafish genome GRCz10 as well as gene annotation Ensembl 87 were downloaded from Ensembl and the annotation was filtered with the \u2018mkgtf\u2019 command of Cell Ranger options: \u2018  attribute=gene biotype:protein coding   attribute=gene biotype:lincRNA \u2013attribute=gene biotype:antisense\u2019. Genome sequence and filtered annotation were then used as input to the \u2018mkref\u2019 command of Cell Ranger to build the appropriate Cellranger Reference. Genome build: Zebrafish GRCz10 Supplementary files format and content: csv format with rows as genes and columns as cells", "pancreatic cells", null, "Enzymatic Dissociation The single cell suspension was adjusted to a concentration of about 800 cells per microliter and diluted with nuclease free water according to the manufacturer\u2019s instructions to yield 5000 cells. Subsequently  the cells were carefully mixed with reverse transcription mix before loading the cells on the 10X Genomics Chromium system Zheng et al.  2016.  post the gel emulsion bead suspension underwent the reverse transcription reaction  emulsion was broken and DNA purified using Silane beads. The cDNA was amplified with 10 cycles  following the guidelines of the 10x Genomics user manual.  The 10X Genomics single cell RNA seq library preparation   involving fragmentation  dA Tailing  adapter ligation and indexing PCR \u2013 was performed based on the manufacturer\u2019s protocol.", null, "age:2mpf|strain:Tgins:BB1.0L|disease state:Normal", "GSM3509161", "GSM3509161: 2mpf Pancreas; Danio rerio; RNA Seq", "GSM3509161", null, "1", "Enzymatic Dissociation The single cell suspension was adjusted to a concentration of about 800 cells per microliter and diluted with nuclease free water according to the manufacturer's instructions to yield 5000 cells. Subsequently  the cells were carefully mixed with reverse transcription mix before loading the cells on the 10X Genomics Chromium system Zheng et al.  2016.  post the gel emulsion bead suspension underwent the reverse transcription reaction  emulsion was broken and DNA purified using Silane beads. The cDNA was amplified with 10 cycles  following the guidelines of the 10x Genomics user manual.  The 10X Genomics single cell RNA seq library preparation   involving fragmentation  dA Tailing  adapter ligation and indexing PCR \u2013 was performed based on the manufacturer's protocol.", "GEO Accession:GSM3509161", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 550", null, "SRP173304", null, null, "s2mpf_R1.fastq.gz s2mpf_R2.fastq.gz", "fastq fastq", 3682641276.0, 44369172.0, "GSM3509161 r1", "0:26 1:57", "A:950388419;C:876060179;G:944476013;T:911635661;N:81004", 26, 57, null, null, 950388419, 876060179, 944476013, 911635661, 81004, "SRX5126276", "SRS4139398", "SRA822849", "GEO", "Single Cell Endocrinology, IRIBHM", 2, 0.00373, 0.9564, 0.0008, 0.03195, 0.99508, 0.9024, 0.38273, 0.59374, 26, 57, "T", "B", "sc-like readlen", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Belgium", "2018-12-11", "Juvenile", "Juvenile", "Pancreas", "Endocrine System"], [63128, "SRR13616487", "SRX10009741", "SRS8178664", "SRP304424", "PRJNA699078", "Single cell RNA sequencing of zebrafish pancreatic cells during beta cell regeneration", "GSE166052", "Transcriptome Analysis", "To better understand the underlying mechanism of beta cell regeneration in adult zebrafish  we performed single cell transcriptomic profiling of the pancreatic tissue using 10X Genomics at various stages post beta cell ablation. Overall design: The adult fish expressing NTR gene under the insulin promoter were treated with Mtz Sigma Aldrich  M3761  dissolved at 10mM concentration in fish water. The animals were treated for 24 hours  protected from light. post 24h  Mtz solution was removed and the animals were placed 3 times in fresh fish water before returning them to standard maintenance conditions. Both untreated and Mtz treated animals were euthanized by an overdose of tricaine. Samples for each time point comprised of 6 animals 3 males and 3 females. Single cell suspension was prepared and 15000 live cells/per condition were FACS sorted for 10X Genomics.", null, "pubmed:35088828", null, "Pancreas 14dpa", "GSM5060849", null, "tissue:Zebrafish pancreas|strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 14 days post MTZ", "Pancreas 14dpa", "bcl2fastq 1: Pancreas Control  Pancreas 2dpa and Pancreas 7dpa were run with bcl2fastq2 2.19.1. bcl2fastq 2: Pancreas 0dap and Pancreas 14dpa were run with bcl2fastq2 2.20.0. Reference build: Cellranger needs a reference. Here GRCz11 was used and 3 transgenic genes were added to avoid false alignments to the main references. The genes are YFP  mCherry and NTR. Alignment: Processing of sequencing data was done with the cellranger pipeline cellranger 4.0.0. Genome build: GRCz11 Supplementary files format and content: Tar archives contain the cellranger filtered feature barcode folder; the 3 files per folder are explained here: https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/output/matrices", "Zebrafish pancreas", null, "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", null, "strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:Pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 14 days post MTZ", "GSM5060849", "GSM5060849: Pancreas 14dpa; Danio rerio; RNA Seq", "GSM5060849", null, "1", "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", "GEO Accession:GSM5060849", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP304424", null, null, "L59491_Track-100378_R1.fastq.gz L59491_Track-100378_R2.fastq.gz", "fastq fastq", 21882647280.0, 168328056.0, "GSM5060849 r1", "0:29 1:101", "A:5304415368;C:5193690448;G:5721535951;T:5662241808;N:763705", 29, 101, null, null, 5304415368, 5193690448, 5721535951, 5662241808, 763705, "SRX10009741", "SRS8178664", "SRA1190924", "GEO", "Ninov Lab, CRTD, TU Dresden", 2, 0.0137, 0.94318, 0.00185, 0.03707, 0.99263, 0.91078, 0.60061, 0.58256, 29, 101, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2021-02-02", "Adult", "Adult", "Pancreas", "Endocrine System"], [63129, "SRR13616486", "SRX10009740", "SRS8178663", "SRP304424", "PRJNA699078", "Single cell RNA sequencing of zebrafish pancreatic cells during beta cell regeneration", "GSE166052", "Transcriptome Analysis", "To better understand the underlying mechanism of beta cell regeneration in adult zebrafish  we performed single cell transcriptomic profiling of the pancreatic tissue using 10X Genomics at various stages post beta cell ablation. Overall design: The adult fish expressing NTR gene under the insulin promoter were treated with Mtz Sigma Aldrich  M3761  dissolved at 10mM concentration in fish water. The animals were treated for 24 hours  protected from light. post 24h  Mtz solution was removed and the animals were placed 3 times in fresh fish water before returning them to standard maintenance conditions. Both untreated and Mtz treated animals were euthanized by an overdose of tricaine. Samples for each time point comprised of 6 animals 3 males and 3 females. Single cell suspension was prepared and 15000 live cells/per condition were FACS sorted for 10X Genomics.", null, "pubmed:35088828", null, "Pancreas 7dpa", "GSM5060848", null, "tissue:Zebrafish pancreas|strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 7 days post MTZ", "Pancreas 7dpa", "bcl2fastq 1: Pancreas Control  Pancreas 2dpa and Pancreas 7dpa were run with bcl2fastq2 2.19.1. bcl2fastq 2: Pancreas 0dap and Pancreas 14dpa were run with bcl2fastq2 2.20.0. Reference build: Cellranger needs a reference. Here GRCz11 was used and 3 transgenic genes were added to avoid false alignments to the main references. The genes are YFP  mCherry and NTR. Alignment: Processing of sequencing data was done with the cellranger pipeline cellranger 4.0.0. Genome build: GRCz11 Supplementary files format and content: Tar archives contain the cellranger filtered feature barcode folder; the 3 files per folder are explained here: https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/output/matrices", "Zebrafish pancreas", null, "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", null, "strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:Pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 7 days post MTZ", "GSM5060848", "GSM5060848: Pancreas 7dpa; Danio rerio; RNA Seq", "GSM5060848", null, "1", "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", "GEO Accession:GSM5060848", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP304424", null, null, "L47897_Track-91889_R1.fastq.gz L47897_Track-91889_R2.fastq.gz", "fastq fastq", 11982402020.0, 98216410.0, "GSM5060848 r1", "0:29 1:93", "A:3162707284;C:2774571882;G:2736678637;T:3307378654;N:1065563", 29, 93, null, null, 3162707284, 2774571882, 2736678637, 3307378654, 1065563, "SRX10009740", "SRS8178663", "SRA1190924", "GEO", "Ninov Lab, CRTD, TU Dresden", 2, 0.01025, 0.93044, 0.00221, 0.066, 0.98938, 0.85823, 0.52941, 0.62147, 29, 93, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2021-02-02", "Adult", "Adult", "Pancreas", "Endocrine System"], [63130, "SRR13616485", "SRX10009739", "SRS8178662", "SRP304424", "PRJNA699078", "Single cell RNA sequencing of zebrafish pancreatic cells during beta cell regeneration", "GSE166052", "Transcriptome Analysis", "To better understand the underlying mechanism of beta cell regeneration in adult zebrafish  we performed single cell transcriptomic profiling of the pancreatic tissue using 10X Genomics at various stages post beta cell ablation. Overall design: The adult fish expressing NTR gene under the insulin promoter were treated with Mtz Sigma Aldrich  M3761  dissolved at 10mM concentration in fish water. The animals were treated for 24 hours  protected from light. post 24h  Mtz solution was removed and the animals were placed 3 times in fresh fish water before returning them to standard maintenance conditions. Both untreated and Mtz treated animals were euthanized by an overdose of tricaine. Samples for each time point comprised of 6 animals 3 males and 3 females. Single cell suspension was prepared and 15000 live cells/per condition were FACS sorted for 10X Genomics.", null, "pubmed:35088828", null, "Pancreas 2dpa", "GSM5060847", null, "tissue:Zebrafish pancreas|strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 2 days post MTZ", "Pancreas 2dpa", "bcl2fastq 1: Pancreas Control  Pancreas 2dpa and Pancreas 7dpa were run with bcl2fastq2 2.19.1. bcl2fastq 2: Pancreas 0dap and Pancreas 14dpa were run with bcl2fastq2 2.20.0. Reference build: Cellranger needs a reference. Here GRCz11 was used and 3 transgenic genes were added to avoid false alignments to the main references. The genes are YFP  mCherry and NTR. Alignment: Processing of sequencing data was done with the cellranger pipeline cellranger 4.0.0. Genome build: GRCz11 Supplementary files format and content: Tar archives contain the cellranger filtered feature barcode folder; the 3 files per folder are explained here: https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/output/matrices", "Zebrafish pancreas", null, "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", null, "strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:Pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 2 days post MTZ", "GSM5060847", "GSM5060847: Pancreas 2dpa; Danio rerio; RNA Seq", "GSM5060847", null, "1", "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", "GEO Accession:GSM5060847", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP304424", null, null, "L47899_Track-88823_R1.fastq.gz L47899_Track-88823_R2.fastq.gz", "fastq fastq", 12079250378.0, 99010249.0, "GSM5060847 r1", "0:29 1:93", "A:3187642396;C:2755358695;G:2795295173;T:3340653508;N:300606", 29, 93, null, null, 3187642396, 2755358695, 2795295173, 3340653508, 300606, "SRX10009739", "SRS8178662", "SRA1190924", "GEO", "Ninov Lab, CRTD, TU Dresden", 2, 0.00631, 0.94202, 0.00135, 0.0615, 0.99123, 0.84307, 0.55742, 0.56593, 29, 93, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2021-02-02", "Adult", "Adult", "Pancreas", "Endocrine System"], [63131, "SRR13616484", "SRX10009738", "SRS8178661", "SRP304424", "PRJNA699078", "Single cell RNA sequencing of zebrafish pancreatic cells during beta cell regeneration", "GSE166052", "Transcriptome Analysis", "To better understand the underlying mechanism of beta cell regeneration in adult zebrafish  we performed single cell transcriptomic profiling of the pancreatic tissue using 10X Genomics at various stages post beta cell ablation. Overall design: The adult fish expressing NTR gene under the insulin promoter were treated with Mtz Sigma Aldrich  M3761  dissolved at 10mM concentration in fish water. The animals were treated for 24 hours  protected from light. post 24h  Mtz solution was removed and the animals were placed 3 times in fresh fish water before returning them to standard maintenance conditions. Both untreated and Mtz treated animals were euthanized by an overdose of tricaine. Samples for each time point comprised of 6 animals 3 males and 3 females. Single cell suspension was prepared and 15000 live cells/per condition were FACS sorted for 10X Genomics.", null, "pubmed:35088828", null, "Pancreas 0dpa", "GSM5060846", null, "tissue:Zebrafish pancreas|strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 0 days post MTZ", "Pancreas 0dpa", "bcl2fastq 1: Pancreas Control  Pancreas 2dpa and Pancreas 7dpa were run with bcl2fastq2 2.19.1. bcl2fastq 2: Pancreas 0dap and Pancreas 14dpa were run with bcl2fastq2 2.20.0. Reference build: Cellranger needs a reference. Here GRCz11 was used and 3 transgenic genes were added to avoid false alignments to the main references. The genes are YFP  mCherry and NTR. Alignment: Processing of sequencing data was done with the cellranger pipeline cellranger 4.0.0. Genome build: GRCz11 Supplementary files format and content: Tar archives contain the cellranger filtered feature barcode folder; the 3 files per folder are explained here: https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/output/matrices", "Zebrafish pancreas", null, "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", null, "strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:Pooled male and female|age:Adult|treatment:MTZ treatment for 24 hours|time point:Dissection at 0 days post MTZ", "GSM5060846", "GSM5060846: Pancreas 0dpa; Danio rerio; RNA Seq", "GSM5060846", null, "1", "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", "GEO Accession:GSM5060846", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP304424", null, null, "L59306_Track-100369_R1.fastq.gz L59306_Track-100369_R2.fastq.gz", "fastq fastq", 19138165410.0, 147216657.0, "GSM5060846 r1", "0:29 1:101", "A:4905247743;C:4584481588;G:4969548524;T:4678220753;N:666802", 29, 101, null, null, 4905247743, 4584481588, 4969548524, 4678220753, 666802, "SRX10009738", "SRS8178661", "SRA1190924", "GEO", "Ninov Lab, CRTD, TU Dresden", 2, 0.02866, 0.88637, 0.00798, 0.14499, 0.99105, 0.87251, 0.51922, 0.57508, 29, 101, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2021-02-02", "Adult", "Adult", "Pancreas", "Endocrine System"], [63132, "SRR13616483", "SRX10009737", "SRS8178660", "SRP304424", "PRJNA699078", "Single cell RNA sequencing of zebrafish pancreatic cells during beta cell regeneration", "GSE166052", "Transcriptome Analysis", "To better understand the underlying mechanism of beta cell regeneration in adult zebrafish  we performed single cell transcriptomic profiling of the pancreatic tissue using 10X Genomics at various stages post beta cell ablation. Overall design: The adult fish expressing NTR gene under the insulin promoter were treated with Mtz Sigma Aldrich  M3761  dissolved at 10mM concentration in fish water. The animals were treated for 24 hours  protected from light. post 24h  Mtz solution was removed and the animals were placed 3 times in fresh fish water before returning them to standard maintenance conditions. Both untreated and Mtz treated animals were euthanized by an overdose of tricaine. Samples for each time point comprised of 6 animals 3 males and 3 females. Single cell suspension was prepared and 15000 live cells/per condition were FACS sorted for 10X Genomics.", null, "pubmed:35088828", null, "Pancreas Control", "GSM5060845", null, "tissue:Zebrafish pancreas|strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:pooled male and female|age:Adult|treatment:Untreated|time point:Untreated", "Pancreas Control", "bcl2fastq 1: Pancreas Control  Pancreas 2dpa and Pancreas 7dpa were run with bcl2fastq2 2.19.1. bcl2fastq 2: Pancreas 0dap and Pancreas 14dpa were run with bcl2fastq2 2.20.0. Reference build: Cellranger needs a reference. Here GRCz11 was used and 3 transgenic genes were added to avoid false alignments to the main references. The genes are YFP  mCherry and NTR. Alignment: Processing of sequencing data was done with the cellranger pipeline cellranger 4.0.0. Genome build: GRCz11 Supplementary files format and content: Tar archives contain the cellranger filtered feature barcode folder; the 3 files per folder are explained here: https://support.10xgenomics.com/single cell gene expression/software/pipelines/latest/output/matrices", "Zebrafish pancreas", null, "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", null, "strain/background:AB|genotype/variation:Wildtype  expressing NTR gene under the insulin promoter|cell type:Pancreatic cells|Sex:Pooled male and female|age:Adult|treatment:Untreated|time point:Untreated", "GSM5060845", "GSM5060845: Pancreas Control; Danio rerio; RNA Seq", "GSM5060845", null, "1", "Trypsin based dissociation followed by FACS sorting of alive cells. Library prep was performed according to the 10x protocol.", "GEO Accession:GSM5060845", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP304424", null, null, "L47898_Track-88822_R1.fastq.gz L47898_Track-88822_R2.fastq.gz", "fastq fastq", 8952747472.0, 73383176.0, "GSM5060845 r1", "0:29 1:93", "A:2223721886;C:2087634305;G:2235052745;T:2406116444;N:222092", 29, 93, null, null, 2223721886, 2087634305, 2235052745, 2406116444, 222092, "SRX10009737", "SRS8178660", "SRA1190924", "GEO", "Ninov Lab, CRTD, TU Dresden", 2, 0.00837, 0.9475, 0.00144, 0.0366, 0.99263, 0.88759, 0.58964, 0.57851, 29, 93, "T", "B", "sc-like readlen", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Germany", "2021-02-02", "Adult", "Adult", "Pancreas", "Endocrine System"]], "truncated": false, "filtered_table_rows_count": 8, "expanded_columns": [], "expandable_columns": [], "columns": ["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"], "primary_keys": [], "units": {}, "query": {"sql": "select 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 from run_metadata where \"experiment.library_source\" = :p0 and \"technology\" = :p1 and \"tissue_curation\" = :p2 order by rowid limit 101", "params": {"p0": "TRANSCRIPTOMIC", "p1": "10x", "p2": "Pancreas"}}, "facet_results": {"experiment.library_strategy": {"name": "experiment.library_strategy", "type": "column", "hideable": false, "toggle_url": "/metadata/run_metadata.json?experiment.library_source=TRANSCRIPTOMIC&technology=10x&tissue_curation=Pancreas", "results": [{"value": "RNA-Seq", "label": "RNA-Seq", "count": 7, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?experiment.library_source=TRANSCRIPTOMIC&technology=10x&tissue_curation=Pancreas&experiment.library_strategy=RNA-Seq", "selected": false}, {"value": "OTHER", "label": "OTHER", "count": 1, "toggle_url": 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