metadata: run_metadata: 8 rows where experiment.library_selection = "size fractionation", technology = "bulk" and tissue_curation

8 rows where experiment.library_selection = "size fractionation", technology = "bulk" and tissue_curation_coarse = "Cardiovascular System"

descending

Link	rowid ▼	run.accession	experiment.accession	sample.accession	study.accession	bioproject	study.title	study.alias	study.type	study.abstract	study.attributes	study.PMIDs	sample.title	sample.alias	sample.attributes	GEOsample.title	GEOsample.dataprocessing	GEOsample.source	GEOsample.extractprotocol	GEOsample.characteristics	GEOsample.accession	experiment.title	experiment.alias	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.study_ref	run.filename	run.semantic_name	run.total_bases	run.total_spots	run.alias	run.read_lengths	run.base_counts	run.r1_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.nofeature_rate.mate1	seqdetective.sparsity.mate1	seqdetective.pos_strand_rate.mate1	seqdetective.readlen.mate1	seqdetective.judgement.mate1	seqdetective.judgement.reason	platform_family	instrument_generation	read_bias	selection_class	prep_kit	sc_or_bulk	tech_class	technology	submission.bioprojectsource.country	earliest_date	devstage_curation	devstage_curation_coarse	tissue_curation	tissue_curation_coarse
37134	37134	SRR997335	SRX355601	SRS483796	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Control rep4	GSM1234963	source name:Heart Control\|tissue:heart	Heart Control rep4	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234963	GSM1234963: Heart Control rep4; Danio rerio; RNA Seq	GSM1234963	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234963	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	C3PO_0053_s_7_sequence.txt.gz	fastq	1111882122.0	28509798.0	GSM1234963 r1	0:39	A:239964076;C:229590501;G:337557042;T:303257677;N:1512826	39	239964076	229590501	337557042	303257677	1512826	SRX355601	SRS483796	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.11195	0.03776	0.98871	0.16576	39	B	usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37135	37135	SRR997334	SRX355600	SRS483795	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Control rep3	GSM1234962	source name:Heart Control\|tissue:heart	Heart Control rep3	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234962	GSM1234962: Heart Control rep3; Danio rerio; RNA Seq	GSM1234962	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234962	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	C3PO_0053_s_6_sequence.txt.gz	fastq	1221305046.0	31315514.0	GSM1234962 r1	0:39	A:263520584;C:251263128;G:372262308;T:332218529;N:2040497	39	263520584	251263128	372262308	332218529	2040497	SRX355600	SRS483795	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.11552	0.03865	0.98679	0.1927	39	B	usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37136	37136	SRR997333	SRX355599	SRS483794	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Control rep2	GSM1234961	source name:Heart Control\|tissue:heart	Heart Control rep2	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234961	GSM1234961: Heart Control rep2; Danio rerio; RNA Seq	GSM1234961	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234961	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	R2D2_0122_s_7_sequence.txt.gz	fastq	1462542939.0	37501101.0	GSM1234961 r1	0:39	A:313173840;C:298865755;G:440814004;T:409066990;N:622350	39	313173840	298865755	440814004	409066990	622350	SRX355599	SRS483794	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.01745	0.00554	0.99101	0.42928	39	B	usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37137	37137	SRR997332	SRX355598	SRS483793	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Control rep1	GSM1234960	source name:Heart Control\|tissue:heart	Heart Control rep1	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Control	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234960	GSM1234960: Heart Control rep1; Danio rerio; RNA Seq	GSM1234960	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234960	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	R2D2_0122_s_6_sequence.txt.gz	fastq	1447346355.0	37111445.0	GSM1234960 r1	0:39	A:311132663;C:297266985;G:441400778;T:396960907;N:585022	39	311132663	297266985	441400778	396960907	585022	SRX355598	SRS483793	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.06118	0.01997	0.98752	0.43741	39	B	usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37138	37138	SRR997331	SRX355597	SRS483792	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Resected rep4	GSM1234959	source name:Heart Resected\|tissue:heart	Heart Resected rep4	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234959	GSM1234959: Heart Resected rep4; Danio rerio; RNA Seq	GSM1234959	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234959	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	C3PO_0053_s_5_sequence.txt.gz	fastq	703519557.0	18038963.0	GSM1234959 r1	0:39	A:142685665;C:144259439;G:215526965;T:199924689;N:1122799	39	142685665	144259439	215526965	199924689	1122799	SRX355597	SRS483792	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.00172	0.00045	0.99738	0.34873	39	T	under 1.2% mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37139	37139	SRR997330	SRX355596	SRS483791	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Resected rep3	GSM1234958	source name:Heart Resected\|tissue:heart	Heart Resected rep3	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234958	GSM1234958: Heart Resected rep3; Danio rerio; RNA Seq	GSM1234958	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234958	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	C3PO_0053_s_4_sequence.txt.gz	fastq	918978177.0	23563543.0	GSM1234958 r1	0:39	A:188056254;C:191217660;G:283318445;T:255042736;N:1343082	39	188056254	191217660	283318445	255042736	1343082	SRX355596	SRS483791	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.09453	0.03085	0.98559	0.18337	39	B	usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37140	37140	SRR997329	SRX355595	SRS483789	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Resected rep2	GSM1234957	source name:Heart Resected\|tissue:heart	Heart Resected rep2	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234957	GSM1234957: Heart Resected rep2; Danio rerio; RNA Seq	GSM1234957	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234957	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	R2D2_0122_s_5_sequence.txt.gz	fastq	1420874247.0	36432673.0	GSM1234957 r1	0:39	A:290914118;C:295973738;G:440368910;T:393019696;N:597785	39	290914118	295973738	440368910	393019696	597785	SRX355595	SRS483789	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.00472	0.00131	0.99431	0.42832	39	T	under 1.2% mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular System
37141	37141	SRR997328	SRX355594	SRS483790	SRP030036	PRJNA219641	Comparative transcriptome profiling of the injured zebrafish and mouse hearts identifies miRNA dependent repair pathways	GSE51018	Transcriptome Analysis	The mammalian heart has poor regenerative capacity following injury. In contrast certain lower vertebrates such as zebrafish retain a robust capacity for regeneration into adult life. Here we use an integrated approach to identify evolutionary conserved regenerative miRNA dependant regulatory circuits in the heart. We identified novel miRNA dependant networks involved in critical biological pathways which are differentially utilized between the infarcted mouse heart and the regenerating zebrafish heart. Overall design: 2 conditions 4 biological replicates per condition	parent bioproject:PRJNA219631	pubmed:26857418	Heart Resected rep1	GSM1234956	source name:Heart Resected\|tissue:heart	Heart Resected rep1	Base calling was with Illumina GAP Pipeline Software v1.70 Sequence reads were processed to remove the adaptor sequences and reformatted to FASTA files using the FASTX Toolkit Sequences were aligned to mouse mature microRNA sequences from miRBase Version 17 and non coding RNA sequences Rfam Version 10 using MEGABLAST with a word size of 8 nucleotides. The criteria for counting a sequence match were if the % query was >=90% of the target sequence and if there were <= 2 mismatches over the alignment. The % query was calculated as a/q x p where a= alignment length q= query length and p= percent identity over aligned region. The matches against miRBase were parsed and the top matches based on % query were selected. If a sequence had more than one top match against different database sequences it was excluded from the subsequent analysis. Matches to Rfam were only taken into account for sequences not matching miRBase. Genome build: miRBase17 Supplementary files format and content: Raw count data for microRNAs were normalized to the relative size of each library using R/Bioconductor package DESeq estimateSizeFactors function. Count data are provided in tab delimited format	Heart Resected	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	tissue:heart	GSM1234956	GSM1234956: Heart Resected rep1; Danio rerio; RNA Seq	GSM1234956	1	Total RNA was isolated using Trizol Invitrogen. RNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 BioanalyzerRNA quantities and quality were assessed using a NanoDrop ND 1000 spectrophotometer or an Agilent 2100 Bioanalyzer. Libraries of small RNAs for sequencing were prepared using the DGE Small RNA Sample Kit Alternative v1.5 Protocol Illumina; San Diego California according to the protocol supplied with the reagents Protocol Rev. A published February 2009 and using 1ug of total RNA. One lane of each library was sequenced on the Genome Analyzer IIx Illumina using the 36 Cycle Sequencing Kit v5 and v4 flowcell and cluster reagents Catalog FC 104 5020 and GD 300 1001	GEO Accession:GSM1234956	RNA-Seq	TRANSCRIPTOMIC	size fractionation	SINGLE	ILLUMINA	Illumina Genome Analyzer II	SRP030036	C3PO_0054_s_8_sequence.txt.gz	fastq	1073339514.0	27521526.0	GSM1234956 r1	0:39	A:223670054;C:219603945;G:328718329;T:300891777;N:455409	39	223670054	219603945	328718329	300891777	455409	SRX355594	SRS483790	SRA101779	GEO	Vital-IT, SIB Swiss Institute of Bioinformatics	1	0.05133	0.01643	0.9893	0.25792	39	B	usable mapping rate	illumina	early_illumina	unknown	size_fractionation	unknown	bulk	bulk	bulk	Switzerland	2013-09-19	Undetermined	Undetermined	Heart	Cardiovascular 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");;