{"database": "metadata", "table": "run_metadata", "is_view": false, "human_description_en": "where experiment.library_source = \"TRANSCRIPTOMIC\", technology = \"10x\" and tissue_curation = \"Liver\"", "rows": [[55196, "SRR10153191", "SRX6878621", "SRS5414403", "SRP222786", "PRJNA573063", "Single cell transcriptomic analysis of two models of zebrafish beta catenin driven HCC", "GSE137784", "Transcriptome Analysis", "Up to 41% of hepatocellular carcinomas HCCs result from activating mutations in the CTNNB1 gene encoding \u00df catenin. \u00df catenin has dual cellular functions as a component of the Wnt signaling pathway and adherens junctions. HCC associated CTNNB1 mutations stabilize the \u00df catenin protein  leading to nuclear and/or cytoplasmic localization of \u00df catenin and downstream activation of Wnt target genes. In patient HCC samples  \u00df catenin nuclear and cytoplasmic localization are typically patchy  even among HCC with highly active CTNNB1 mutations. The functional and clinical relevance of this heterogeneity in \u00df catenin activation are not well understood. To define mechanisms of \u00df catenin driven HCC initiation  we generated a Cre lox system that enabled switching on activated \u00df catenin in 1 a small number of hepatocytes in early development; or 2 the majority of hepatocytes in later development or maturity. We discovered that switching on activated \u00df catenin in a subset of larval hepatocytes was sufficient to drive HCC initiation. To determine the role of Wnt/\u00df catenin signaling heterogeneity later in hepatocarcinogenesis  we performed RNA seq analysis of zebrafish \u00df catenin driven HCC. Ingenuity Pathway Analysis of differentially expressed genes in the Cre lox HCC model revealed that \u201cCancer\u201d and \u201cLiver Tumor\u201d categories were significantly altered  indicating transcriptional similarities with human HCC and other vertebrate HCC models. At the single cell level  2.9% to 15.2% of hepatocytes from zebrafish \u00df catenin driven HCC expressed two or more of the Wnt target genes axin2  mtor  glula  myca  and wif1  indicating focal activation of Wnt signaling in established tumors. Thus  heterogeneous \u00df catenin activation drives HCC initiation and persists throughout hepatocarcinogenesis. Overall design: Examination of three 6mpf liver samples from three different transgenic lines with/without xxx hydroxytamoxifen TAM treatment.", "parent bioproject:PRJNA573068", "pubmed:31575545", null, "NoHCC [Single cell]", "GSM4087821", null, "tissue:Liver|transgenic line:Tgfabp10a flox beta catenin|age:6 mpf at larval stg:10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf HCC", "NoHCC [Single cell]", "10x Genomics\u2019 Cell Ranger software v2.2.0 executed primary data analysis for each sample. Pipeline 'cellranger mkfastq' generated R1 26 bp and R2 100 bp  FASTQ files. Custom transgenic genomic reference was built with \u2018cellranger mkref\u2019  but shared the common Danio rerio genome reference build GRCz11 with annotations from Ensembl release 94. The Ensembl gene annotations were filtered with \u2018cellranger mkgtf\u2019 for gene biotypes matching \u2018protein coding\u2019  \u2018lincRNA\u2019 and \u2018antisense\u2019 tags. All samples had additional transgenic sequence/annotations added. Each sample was processed with \u2018cellranger count\u2019 pipeline with their respective transgenic genome build with parameter \u2018  expect cells=3000\u2019 In attempt to recover those perhaps lower quality GEM partitions  the raw gene barcode matrices from \u2018cellranger count\u2019 located in \u2018outs/raw gene bc matrices\u2019 was processed with the EmptyDrops algorithm R package DropletUtils v1.2.2 to discriminate cells from background GEM partitions at a false discovery rate FDR of 1% Lun ATL et al.  2019. GEM partitions with 500 UMI counts or less were considered to be devoid of viable cells  while those with at least 10 000 UMI counts were automatically considered to be cells. Cell based QC metrics were calculated with R package scater v1.10.1 using the calculateQCMetrics function McCarthy DJ et al.  2017. Principal component analysis PCA on the cell based QC metrics combined with a multivariate outlier method flagged cells with outlying values in QC metrics as suspect P. Filzmoser et al.  2008. Cells with extremely low UMI counts  extremely low gene counts or extremely high percentage of expression attributed to mitochondrial genes were also flagged as low quality. Extremeness in any of these three measures was determined by 3 median absolute deviations from the median with the scater::isOutlier function applied to each sample individually. Additionally  cells were required to have greater than 800 UMIs and less than 20% of total expression attributed to mitochondrial transcripts. Those cells suspected of being low quality were removed from downstream analysis. Genome build: GRCz11 Supplementary files format and content: MTX", "Liver", "Larvae for Samples 2 and 3 were treated with 10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf", "Zebrafish were euthanized by rapid chilling and their livers were dissected. Half of each liver was submitted for histologic evaluation to confirm the diagnosis HCC or no HCC. The remaining half of each liver was dissociated into single cell suspensions and prepared for single tube single cell RNA sequencing scRNA seq based on the 10X Genomics platform. Dissected liver tissue was immersed in 5% Fetal Bovine Serum FBS in Hank\u2019s Buffered Saline Solution HBSS without xxx red  with calcium and magnesium and chopped finely. The cells were were homogenized in 1 mL of 0.25% trypsin + EDTA for 5 minutes at room temperature and re suspended in 1 mL of 5%FBS+5mM EDTA in HBSS Free solution. Cells were then filtered through a 40 micron membrane filter  and the filtrate was centrifuged at 1200 RPM  4\uf0b0C for 5 minutes. The cell pellet was then re suspended in phosphate buffered saline with 0.04% bovine serum albumin.  The cell suspension was then filtered again through 40 micron cell strainers to obtain a liver single cell suspension. Viability and cell count were assessed on Countess I Thermo Scientific.  The Chromium Single Cell Gene Expression Solution with 3\u2019 chemistry  version 2 PN 120237 was used to barcode individual cells with 16 bp 10x Barcode and to tag cell specific transcript molecules with 10 bp Unique Molecular Identifier UMI according to the manufactures instruction.  Equilibrium to targeted cell recovery of 6 000 cells along with 10x Gel Beads and reverse transcription reagents were loaded to Chromium Single Cell A Chip PN 120236 to form Gel Bead In EMulsions GEMs  the micro droplets.  Within individual GEMs  cDNA generated from captured and barcoded mRNA was synthesized by reverse transcription at the setting of 53\u00b0C for 45 min followed by 85\u00b0C for 5 min.  Subsequent A tailing  end repair  adaptor ligation and sample indexing was performed in bulk according to the manufacturer's instructions. Multiple libraries were then normalized and sequenced on NovaSeq 6000 with 2x150 PE mode. Single cell three prime RNA Sequencing", "Fish were raised following IACUC approved protocols in insititutional zebrafish facility.", "transgenic line:Tgfabp10a flox beta catenin|age:6 mpf at larval stg:10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf HCC", "GSM4087821", "GSM4087821: NoHCC [Single cell]; Danio rerio; RNA Seq", "GSM4087821", null, "1", "Zebrafish were euthanized by rapid chilling and their livers were dissected. Half of each liver was submitted for histologic evaluation to confirm the diagnosis HCC or no HCC. The remaining half of each liver was dissociated into single cell suspensions and prepared for single tube single cell RNA sequencing scRNA seq based on the 10X Genomics platform. Dissected liver tissue was immersed in 5% Fetal Bovine Serum FBS in Hank's Buffered Saline Solution HBSS without xxx red  with calcium and magnesium and chopped finely. The cells were were homogenized in 1 mL of 0.25% trypsin + EDTA for 5 minutes at room temperature and re suspended in 1 mL of 5%FBS+5mM EDTA in HBSS Free solution. Cells were then filtered through a 40 micron membrane filter  and the filtrate was centrifuged at 1200 RPM  4\uf0b0C for 5 minutes. The cell pellet was then re suspended in phosphate buffered saline with 0.04% bovine serum albumin.  The cell suspension was then filtered again through 40 micron cell strainers to obtain a liver single cell suspension. Viability and cell count were assessed on Countess I Thermo Scientific.  The Chromium Single Cell Gene Expression Solution with three prime chemistry  version 2 PN 120237 was used to barcode individual cells with 16 bp 10x Barcode and to tag cell specific transcript molecules with 10 bp Unique Molecular Identifier UMI according to the manufactures instruction.  Equilibrium to targeted cell recovery of 6 000 cells along with 10x Gel Beads and reverse transcription reagents were loaded to Chromium Single Cell A Chip PN 120236 to form Gel Bead In EMulsions GEMs  the micro droplets.  Within individual GEMs  cDNA generated from captured and barcoded mRNA was synthesized by reverse transcription at the setting of 53\u00b0C for 45 min followed by 85\u00b0C for 5 min.  Subsequent A tailing  end repair  adaptor ligation and sample indexing was performed in bulk according to the manufacturer's instructions. Multiple libraries were then normalized and sequenced on NovaSeq 6000 with 2x150 PE mode. Single cell three prime RNA Sequencing", "GEO Accession:GSM4087821", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP222786", null, null, "15547X4_S11_L007_R2_001.fastq.gz 15547X4_S11_L007_R1_001.fastq.gz", "fastq fastq", 16861988178.0, 133825303.0, "GSM4087821 r1", "0:26 1:100", "A:4788108995;C:3905645218;G:3694064311;T:4468647482;N:5522172", 26, 100, null, null, 4788108995, 3905645218, 3694064311, 4468647482, 5522172, "SRX6878621", "SRS5414403", "SRA965504", "GEO", "Pathology, University of California, San Francisco", 2, 0.00236, 0.93017, 0.0008, 0.04645, 0.99626, 0.89043, 0.52233, 0.64352, 26, 100, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-09-20", "Multi-stage", "Multi-stage", "Liver", "Liver and Biliary System"], [55197, "SRR10153190", "SRX6878620", "SRS5414402", "SRP222786", "PRJNA573063", "Single cell transcriptomic analysis of two models of zebrafish beta catenin driven HCC", "GSE137784", "Transcriptome Analysis", "Up to 41% of hepatocellular carcinomas HCCs result from activating mutations in the CTNNB1 gene encoding \u00df catenin. \u00df catenin has dual cellular functions as a component of the Wnt signaling pathway and adherens junctions. HCC associated CTNNB1 mutations stabilize the \u00df catenin protein  leading to nuclear and/or cytoplasmic localization of \u00df catenin and downstream activation of Wnt target genes. In patient HCC samples  \u00df catenin nuclear and cytoplasmic localization are typically patchy  even among HCC with highly active CTNNB1 mutations. The functional and clinical relevance of this heterogeneity in \u00df catenin activation are not well understood. To define mechanisms of \u00df catenin driven HCC initiation  we generated a Cre lox system that enabled switching on activated \u00df catenin in 1 a small number of hepatocytes in early development; or 2 the majority of hepatocytes in later development or maturity. We discovered that switching on activated \u00df catenin in a subset of larval hepatocytes was sufficient to drive HCC initiation. To determine the role of Wnt/\u00df catenin signaling heterogeneity later in hepatocarcinogenesis  we performed RNA seq analysis of zebrafish \u00df catenin driven HCC. Ingenuity Pathway Analysis of differentially expressed genes in the Cre lox HCC model revealed that \u201cCancer\u201d and \u201cLiver Tumor\u201d categories were significantly altered  indicating transcriptional similarities with human HCC and other vertebrate HCC models. At the single cell level  2.9% to 15.2% of hepatocytes from zebrafish \u00df catenin driven HCC expressed two or more of the Wnt target genes axin2  mtor  glula  myca  and wif1  indicating focal activation of Wnt signaling in established tumors. Thus  heterogeneous \u00df catenin activation drives HCC initiation and persists throughout hepatocarcinogenesis. Overall design: Examination of three 6mpf liver samples from three different transgenic lines with/without xxx hydroxytamoxifen TAM treatment.", "parent bioproject:PRJNA573068", "pubmed:31575545", null, "HCCCreLox [Single cell]", "GSM4087820", null, "tissue:Liver|transgenic line:Tgfabp10a CreERT2;fabp10a flox beta catenin|age:6 mpf at larval stg:10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf", "HCCCreLox [Single cell]", "10x Genomics\u2019 Cell Ranger software v2.2.0 executed primary data analysis for each sample. Pipeline 'cellranger mkfastq' generated R1 26 bp and R2 100 bp  FASTQ files. Custom transgenic genomic reference was built with \u2018cellranger mkref\u2019  but shared the common Danio rerio genome reference build GRCz11 with annotations from Ensembl release 94. The Ensembl gene annotations were filtered with \u2018cellranger mkgtf\u2019 for gene biotypes matching \u2018protein coding\u2019  \u2018lincRNA\u2019 and \u2018antisense\u2019 tags. All samples had additional transgenic sequence/annotations added. Each sample was processed with \u2018cellranger count\u2019 pipeline with their respective transgenic genome build with parameter \u2018  expect cells=3000\u2019 In attempt to recover those perhaps lower quality GEM partitions  the raw gene barcode matrices from \u2018cellranger count\u2019 located in \u2018outs/raw gene bc matrices\u2019 was processed with the EmptyDrops algorithm R package DropletUtils v1.2.2 to discriminate cells from background GEM partitions at a false discovery rate FDR of 1% Lun ATL et al.  2019. GEM partitions with 500 UMI counts or less were considered to be devoid of viable cells  while those with at least 10 000 UMI counts were automatically considered to be cells. Cell based QC metrics were calculated with R package scater v1.10.1 using the calculateQCMetrics function McCarthy DJ et al.  2017. Principal component analysis PCA on the cell based QC metrics combined with a multivariate outlier method flagged cells with outlying values in QC metrics as suspect P. Filzmoser et al.  2008. Cells with extremely low UMI counts  extremely low gene counts or extremely high percentage of expression attributed to mitochondrial genes were also flagged as low quality. Extremeness in any of these three measures was determined by 3 median absolute deviations from the median with the scater::isOutlier function applied to each sample individually. Additionally  cells were required to have greater than 800 UMIs and less than 20% of total expression attributed to mitochondrial transcripts. Those cells suspected of being low quality were removed from downstream analysis. Genome build: GRCz11 Supplementary files format and content: MTX", "Liver", "Larvae for Samples 2 and 3 were treated with 10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf", "Zebrafish were euthanized by rapid chilling and their livers were dissected. Half of each liver was submitted for histologic evaluation to confirm the diagnosis HCC or no HCC. The remaining half of each liver was dissociated into single cell suspensions and prepared for single tube single cell RNA sequencing scRNA seq based on the 10X Genomics platform. Dissected liver tissue was immersed in 5% Fetal Bovine Serum FBS in Hank\u2019s Buffered Saline Solution HBSS without xxx red  with calcium and magnesium and chopped finely. The cells were were homogenized in 1 mL of 0.25% trypsin + EDTA for 5 minutes at room temperature and re suspended in 1 mL of 5%FBS+5mM EDTA in HBSS Free solution. Cells were then filtered through a 40 micron membrane filter  and the filtrate was centrifuged at 1200 RPM  4\uf0b0C for 5 minutes. The cell pellet was then re suspended in phosphate buffered saline with 0.04% bovine serum albumin.  The cell suspension was then filtered again through 40 micron cell strainers to obtain a liver single cell suspension. Viability and cell count were assessed on Countess I Thermo Scientific.  The Chromium Single Cell Gene Expression Solution with 3\u2019 chemistry  version 2 PN 120237 was used to barcode individual cells with 16 bp 10x Barcode and to tag cell specific transcript molecules with 10 bp Unique Molecular Identifier UMI according to the manufactures instruction.  Equilibrium to targeted cell recovery of 6 000 cells along with 10x Gel Beads and reverse transcription reagents were loaded to Chromium Single Cell A Chip PN 120236 to form Gel Bead In EMulsions GEMs  the micro droplets.  Within individual GEMs  cDNA generated from captured and barcoded mRNA was synthesized by reverse transcription at the setting of 53\u00b0C for 45 min followed by 85\u00b0C for 5 min.  Subsequent A tailing  end repair  adaptor ligation and sample indexing was performed in bulk according to the manufacturer's instructions. Multiple libraries were then normalized and sequenced on NovaSeq 6000 with 2x150 PE mode. Single cell three prime RNA Sequencing", "Fish were raised following IACUC approved protocols in insititutional zebrafish facility.", "transgenic line:Tgfabp10a CreERT2;fabp10a flox beta catenin|age:6 mpf at larval stg:10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf", "GSM4087820", "GSM4087820: HCCCreLox [Single cell]; Danio rerio; RNA Seq", "GSM4087820", null, "1", "Zebrafish were euthanized by rapid chilling and their livers were dissected. Half of each liver was submitted for histologic evaluation to confirm the diagnosis HCC or no HCC. The remaining half of each liver was dissociated into single cell suspensions and prepared for single tube single cell RNA sequencing scRNA seq based on the 10X Genomics platform. Dissected liver tissue was immersed in 5% Fetal Bovine Serum FBS in Hank's Buffered Saline Solution HBSS without xxx red  with calcium and magnesium and chopped finely. The cells were were homogenized in 1 mL of 0.25% trypsin + EDTA for 5 minutes at room temperature and re suspended in 1 mL of 5%FBS+5mM EDTA in HBSS Free solution. Cells were then filtered through a 40 micron membrane filter  and the filtrate was centrifuged at 1200 RPM  4\uf0b0C for 5 minutes. The cell pellet was then re suspended in phosphate buffered saline with 0.04% bovine serum albumin.  The cell suspension was then filtered again through 40 micron cell strainers to obtain a liver single cell suspension. Viability and cell count were assessed on Countess I Thermo Scientific.  The Chromium Single Cell Gene Expression Solution with three prime chemistry  version 2 PN 120237 was used to barcode individual cells with 16 bp 10x Barcode and to tag cell specific transcript molecules with 10 bp Unique Molecular Identifier UMI according to the manufactures instruction.  Equilibrium to targeted cell recovery of 6 000 cells along with 10x Gel Beads and reverse transcription reagents were loaded to Chromium Single Cell A Chip PN 120236 to form Gel Bead In EMulsions GEMs  the micro droplets.  Within individual GEMs  cDNA generated from captured and barcoded mRNA was synthesized by reverse transcription at the setting of 53\u00b0C for 45 min followed by 85\u00b0C for 5 min.  Subsequent A tailing  end repair  adaptor ligation and sample indexing was performed in bulk according to the manufacturer's instructions. Multiple libraries were then normalized and sequenced on NovaSeq 6000 with 2x150 PE mode. Single cell three prime RNA Sequencing", "GEO Accession:GSM4087820", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP222786", null, null, "15547X2_S9_L006_R1_001.fastq.gz 15547X2_S9_L006_R2_001.fastq.gz", "fastq fastq", 16758654318.0, 133005193.0, "GSM4087820 r1", "0:26 1:100", "A:4758015356;C:3904784528;G:3787834220;T:4302283542;N:5736672", 26, 100, null, null, 4758015356, 3904784528, 3787834220, 4302283542, 5736672, "SRX6878620", "SRS5414402", "SRA965504", "GEO", "Pathology, University of California, San Francisco", 2, 0.00291, 0.94432, 0.00084, 0.04281, 0.99539, 0.88203, 0.48041, 0.60684, 26, 100, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-09-20", "Multi-stage", "Multi-stage", "Liver", "Liver and Biliary System"], [55198, "SRR10153189", "SRX6878619", "SRS5414401", "SRP222786", "PRJNA573063", "Single cell transcriptomic analysis of two models of zebrafish beta catenin driven HCC", "GSE137784", "Transcriptome Analysis", "Up to 41% of hepatocellular carcinomas HCCs result from activating mutations in the CTNNB1 gene encoding \u00df catenin. \u00df catenin has dual cellular functions as a component of the Wnt signaling pathway and adherens junctions. HCC associated CTNNB1 mutations stabilize the \u00df catenin protein  leading to nuclear and/or cytoplasmic localization of \u00df catenin and downstream activation of Wnt target genes. In patient HCC samples  \u00df catenin nuclear and cytoplasmic localization are typically patchy  even among HCC with highly active CTNNB1 mutations. The functional and clinical relevance of this heterogeneity in \u00df catenin activation are not well understood. To define mechanisms of \u00df catenin driven HCC initiation  we generated a Cre lox system that enabled switching on activated \u00df catenin in 1 a small number of hepatocytes in early development; or 2 the majority of hepatocytes in later development or maturity. We discovered that switching on activated \u00df catenin in a subset of larval hepatocytes was sufficient to drive HCC initiation. To determine the role of Wnt/\u00df catenin signaling heterogeneity later in hepatocarcinogenesis  we performed RNA seq analysis of zebrafish \u00df catenin driven HCC. Ingenuity Pathway Analysis of differentially expressed genes in the Cre lox HCC model revealed that \u201cCancer\u201d and \u201cLiver Tumor\u201d categories were significantly altered  indicating transcriptional similarities with human HCC and other vertebrate HCC models. At the single cell level  2.9% to 15.2% of hepatocytes from zebrafish \u00df catenin driven HCC expressed two or more of the Wnt target genes axin2  mtor  glula  myca  and wif1  indicating focal activation of Wnt signaling in established tumors. Thus  heterogeneous \u00df catenin activation drives HCC initiation and persists throughout hepatocarcinogenesis. Overall design: Examination of three 6mpf liver samples from three different transgenic lines with/without xxx hydroxytamoxifen TAM treatment.", "parent bioproject:PRJNA573068", "pubmed:31575545", null, "HCCHepABC [Single cell]", "GSM4087819", null, "tissue:Liver|transgenic line:Tgfabp10a pt beta catenin|age:6 mpf at larval stg:N1|diagnosis:HCC", "HCCHepABC [Single cell]", "10x Genomics\u2019 Cell Ranger software v2.2.0 executed primary data analysis for each sample. Pipeline 'cellranger mkfastq' generated R1 26 bp and R2 100 bp  FASTQ files. Custom transgenic genomic reference was built with \u2018cellranger mkref\u2019  but shared the common Danio rerio genome reference build GRCz11 with annotations from Ensembl release 94. The Ensembl gene annotations were filtered with \u2018cellranger mkgtf\u2019 for gene biotypes matching \u2018protein coding\u2019  \u2018lincRNA\u2019 and \u2018antisense\u2019 tags. All samples had additional transgenic sequence/annotations added. Each sample was processed with \u2018cellranger count\u2019 pipeline with their respective transgenic genome build with parameter \u2018  expect cells=3000\u2019 In attempt to recover those perhaps lower quality GEM partitions  the raw gene barcode matrices from \u2018cellranger count\u2019 located in \u2018outs/raw gene bc matrices\u2019 was processed with the EmptyDrops algorithm R package DropletUtils v1.2.2 to discriminate cells from background GEM partitions at a false discovery rate FDR of 1% Lun ATL et al.  2019. GEM partitions with 500 UMI counts or less were considered to be devoid of viable cells  while those with at least 10 000 UMI counts were automatically considered to be cells. Cell based QC metrics were calculated with R package scater v1.10.1 using the calculateQCMetrics function McCarthy DJ et al.  2017. Principal component analysis PCA on the cell based QC metrics combined with a multivariate outlier method flagged cells with outlying values in QC metrics as suspect P. Filzmoser et al.  2008. Cells with extremely low UMI counts  extremely low gene counts or extremely high percentage of expression attributed to mitochondrial genes were also flagged as low quality. Extremeness in any of these three measures was determined by 3 median absolute deviations from the median with the scater::isOutlier function applied to each sample individually. Additionally  cells were required to have greater than 800 UMIs and less than 20% of total expression attributed to mitochondrial transcripts. Those cells suspected of being low quality were removed from downstream analysis. Genome build: GRCz11 Supplementary files format and content: MTX", "Liver", "Larvae for Samples 2 and 3 were treated with 10micromolar 4 hydroxytamoxifen from 3 dpf to 6 dpf", "Zebrafish were euthanized by rapid chilling and their livers were dissected. Half of each liver was submitted for histologic evaluation to confirm the diagnosis HCC or no HCC. The remaining half of each liver was dissociated into single cell suspensions and prepared for single tube single cell RNA sequencing scRNA seq based on the 10X Genomics platform. Dissected liver tissue was immersed in 5% Fetal Bovine Serum FBS in Hank\u2019s Buffered Saline Solution HBSS without xxx red  with calcium and magnesium and chopped finely. The cells were were homogenized in 1 mL of 0.25% trypsin + EDTA for 5 minutes at room temperature and re suspended in 1 mL of 5%FBS+5mM EDTA in HBSS Free solution. Cells were then filtered through a 40 micron membrane filter  and the filtrate was centrifuged at 1200 RPM  4\uf0b0C for 5 minutes. The cell pellet was then re suspended in phosphate buffered saline with 0.04% bovine serum albumin.  The cell suspension was then filtered again through 40 micron cell strainers to obtain a liver single cell suspension. Viability and cell count were assessed on Countess I Thermo Scientific.  The Chromium Single Cell Gene Expression Solution with 3\u2019 chemistry  version 2 PN 120237 was used to barcode individual cells with 16 bp 10x Barcode and to tag cell specific transcript molecules with 10 bp Unique Molecular Identifier UMI according to the manufactures instruction.  Equilibrium to targeted cell recovery of 6 000 cells along with 10x Gel Beads and reverse transcription reagents were loaded to Chromium Single Cell A Chip PN 120236 to form Gel Bead In EMulsions GEMs  the micro droplets.  Within individual GEMs  cDNA generated from captured and barcoded mRNA was synthesized by reverse transcription at the setting of 53\u00b0C for 45 min followed by 85\u00b0C for 5 min.  Subsequent A tailing  end repair  adaptor ligation and sample indexing was performed in bulk according to the manufacturer's instructions. Multiple libraries were then normalized and sequenced on NovaSeq 6000 with 2x150 PE mode. Single cell three prime RNA Sequencing", "Fish were raised following IACUC approved protocols in insititutional zebrafish facility.", "transgenic line:Tgfabp10a pt beta catenin|age:6 mpf at larval stg:N1|diagnosis:HCC", "GSM4087819", "GSM4087819: HCCHepABC [Single cell]; Danio rerio; RNA Seq", "GSM4087819", null, "1", "Zebrafish were euthanized by rapid chilling and their livers were dissected. Half of each liver was submitted for histologic evaluation to confirm the diagnosis HCC or no HCC. The remaining half of each liver was dissociated into single cell suspensions and prepared for single tube single cell RNA sequencing scRNA seq based on the 10X Genomics platform. Dissected liver tissue was immersed in 5% Fetal Bovine Serum FBS in Hank's Buffered Saline Solution HBSS without xxx red  with calcium and magnesium and chopped finely. The cells were were homogenized in 1 mL of 0.25% trypsin + EDTA for 5 minutes at room temperature and re suspended in 1 mL of 5%FBS+5mM EDTA in HBSS Free solution. Cells were then filtered through a 40 micron membrane filter  and the filtrate was centrifuged at 1200 RPM  4\uf0b0C for 5 minutes. The cell pellet was then re suspended in phosphate buffered saline with 0.04% bovine serum albumin.  The cell suspension was then filtered again through 40 micron cell strainers to obtain a liver single cell suspension. Viability and cell count were assessed on Countess I Thermo Scientific.  The Chromium Single Cell Gene Expression Solution with three prime chemistry  version 2 PN 120237 was used to barcode individual cells with 16 bp 10x Barcode and to tag cell specific transcript molecules with 10 bp Unique Molecular Identifier UMI according to the manufactures instruction.  Equilibrium to targeted cell recovery of 6 000 cells along with 10x Gel Beads and reverse transcription reagents were loaded to Chromium Single Cell A Chip PN 120236 to form Gel Bead In EMulsions GEMs  the micro droplets.  Within individual GEMs  cDNA generated from captured and barcoded mRNA was synthesized by reverse transcription at the setting of 53\u00b0C for 45 min followed by 85\u00b0C for 5 min.  Subsequent A tailing  end repair  adaptor ligation and sample indexing was performed in bulk according to the manufacturer's instructions. Multiple libraries were then normalized and sequenced on NovaSeq 6000 with 2x150 PE mode. Single cell three prime RNA Sequencing", "GEO Accession:GSM4087819", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 2500", null, "SRP222786", null, null, "15547X1_S8_L006_R1_001.fastq.gz 15547X1_S8_L006_R2_001.fastq.gz", "fastq fastq", 21400430184.0, 169844684.0, "GSM4087819 r1", "0:26 1:100", "A:6081828690;C:4958144407;G:4770562017;T:5582605586;N:7289484", 26, 100, null, null, 6081828690, 4958144407, 4770562017, 5582605586, 7289484, "SRX6878619", "SRS5414401", "SRA965504", "GEO", "Pathology, University of California, San Francisco", 2, 0.00253, 0.93502, 0.00092, 0.06641, 0.99624, 0.88164, 0.50505, 0.61652, 26, 100, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2019-09-20", "Adult", "Adult", "Liver", "Liver and Biliary System"], [59288, "SRR11806492", "SRX8357870", "SRS6673976", "SRP262133", "PRJNA633496", "Single cell sequencing reveals heterogeneity effects of arsenic or/and 2 2 dichloroacetamide on zebrafish liver", "GSE150751", "Transcriptome Analysis", "Arsenic and DBPs has been found to be one of the major risk in many regions of the world. However  current understanding of thier combined toxicities are unclear. Here we used single cell RNA sequencing to provide the transcriptome heterogeneity of 13563 liver cells obtained from zebrafishes exposed to 100\u00b5g/L arsenic  300\u00b5g/L dichloroacetanilide DCAcAm and co exposure for 23 days. Five liver cell populations were identified. We found that the hepatocytes and macrophages were the main target of arsenic and DCAcAm exposure. And the hepatocytes of male and female showed a huge difference  when expsoure to arsenic and DCAcAm. Overall design: Single cell RNA sequencing were adopted to learn the transcriptional variation in zebrafish liver exposure to arsenic and DCAcAm.", null, null, null, "As Dc", "GSM4558083", null, "source name:liver cells|tissue:liver single cell suspension|age:16 wpf|exposed pollutants:100ug/L arsenic and 300ug/L DCAcAm", "As Dc", "We use FastQC to perform basic statistics on the quality of the raw reads. Then  those read sequences produced by the Illumina pipeline in FASTQ format were pre processed through Trimmomatic software which can be summarized as below:1 Remove low quality reads: scan the read with a 4 base wide sliding window  cutting when the average quality per base drops below 10 SLIDINGWINDOW:  4:10 2 Remove trailing low quality or N bases below quality 3 TRAILING:3 3 Remove adapters : there are two modes to remove the adapter sequence: a.  alignment with the adapter sequence  the number of matching bases were greater than 7 and mismatch=2; b.when read1 and read2 overlapping base scoring  greater than 30  removed non overlapping portions ILLUMINACLIP: adapter.fa:  2: 30: 7 4 Drop reads below the 26 bases long 5 Discard those reads that can not form paired The remaining reads that passed all the filtering steps was counted as clean reads and all subsequent analyses were based on this. At last  we use FastQC to perform basic statistics on the quality of the clean reads. Cell Ranger uses an aligner called STAR  which peforms splicing aware alignment of reads to the genome. Cell Ranger then uses the transcript annotation GTF to bucket the reads into exonic  intronic  and intergenic  and by whether the reads align confidently to the genome. A read is exonic if at least 50% of it intersects an exon  intronic if it is non exonic and intersects an intron  and intergenic otherwise. For reads that align to a single exonic locus but also align to 1 or more non exonic loci  the exonic locus is prioritized and the read is considered to be confidently mapped to the exonic locus with MAPQ 255. Cell Ranger further aligns exonic reads to annotated transcripts  looking for compatibility. A read that is compatible with the exons of an annotated transcript  and aligned to the same strand  is considered mapped to the transcriptome. If the read is compatible with a single gene annotation  it is considered uniquely confidently mapped to the transcriptome. Only reads that  are confidently mapped to the transcriptome are used for UMI counting. Cell Ranger takes as input the expected number of recovered cells  N see    expect cells. Let m be a robust estimate of the maximum total UMI counts  taken as the 99th percentile of the top N barcodes by total UMI counts. All barcodes whose total UMI counts exceed m/10 are called as cells. This is performed separately for each GEM group library and  if the reference contains multiple genomes  for each genome. Genome build: Danio rerio Ensemble 91 Supplementary files format and content: gene barcode expression matrix", "liver cells", "Exposure solutions were prepared by adding 100\u03bcg/L arsenic  300\u03bcg/L DCAcAm or both of them to culture water. The exposure solution were was replaced every 2 days.  post 23 d exposure  zebrafish were collected and liver were rapidly extracted on ice.", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell 3\u2019 Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer\u2019s protocol. Libraries were sequenced on an Illumina Hiseq PE150.", null, "tissue:liver single cell suspension|age:16 wpf|exposed pollutants:100ug/L arsenic and 300ug/L DCAcAm", "GSM4558083", "GSM4558083: As Dc; Danio rerio; RNA Seq", "GSM4558083", null, "1", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell three prime Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer's protocol. Libraries were sequenced on an Illumina Hiseq PE150.", "GEO Accession:GSM4558083", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP262133", null, null, "As_Dc_1.fq.gz As_Dc_2.fq.gz", "fastq fastq", 115893045000.0, 386310150.0, "GSM4558083 r1", "0:150 1:150", "A:28430544743;C:22114323875;G:34731304363;T:30590487752;N:26384267", 150, 150, null, null, 28430544743, 22114323875, 34731304363, 30590487752, 26384267, "SRX8357870", "SRS6673976", "SRA1076689", "GEO", "Nanjing University", 2, 0.0, 0.91666, 0.0, 0.0203, 1.0, 0.91291, null, 0.46748, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2020-05-18", "Adult", "Adult", "Liver", "Liver and Biliary System"], [59289, "SRR11806491", "SRX8357869", "SRS6673975", "SRP262133", "PRJNA633496", "Single cell sequencing reveals heterogeneity effects of arsenic or/and 2 2 dichloroacetamide on zebrafish liver", "GSE150751", "Transcriptome Analysis", "Arsenic and DBPs has been found to be one of the major risk in many regions of the world. However  current understanding of thier combined toxicities are unclear. Here we used single cell RNA sequencing to provide the transcriptome heterogeneity of 13563 liver cells obtained from zebrafishes exposed to 100\u00b5g/L arsenic  300\u00b5g/L dichloroacetanilide DCAcAm and co exposure for 23 days. Five liver cell populations were identified. We found that the hepatocytes and macrophages were the main target of arsenic and DCAcAm exposure. And the hepatocytes of male and female showed a huge difference  when expsoure to arsenic and DCAcAm. Overall design: Single cell RNA sequencing were adopted to learn the transcriptional variation in zebrafish liver exposure to arsenic and DCAcAm.", null, null, null, "Dc300", "GSM4558082", null, "source name:liver cells|tissue:liver single cell suspension|age:16 wpf|exposed pollutants:300ug/L DCAcAm", "Dc300", "We use FastQC to perform basic statistics on the quality of the raw reads. Then  those read sequences produced by the Illumina pipeline in FASTQ format were pre processed through Trimmomatic software which can be summarized as below:1 Remove low quality reads: scan the read with a 4 base wide sliding window  cutting when the average quality per base drops below 10 SLIDINGWINDOW:  4:10 2 Remove trailing low quality or N bases below quality 3 TRAILING:3 3 Remove adapters : there are two modes to remove the adapter sequence: a.  alignment with the adapter sequence  the number of matching bases were greater than 7 and mismatch=2; b.when read1 and read2 overlapping base scoring  greater than 30  removed non overlapping portions ILLUMINACLIP: adapter.fa:  2: 30: 7 4 Drop reads below the 26 bases long 5 Discard those reads that can not form paired The remaining reads that passed all the filtering steps was counted as clean reads and all subsequent analyses were based on this. At last  we use FastQC to perform basic statistics on the quality of the clean reads. Cell Ranger uses an aligner called STAR  which peforms splicing aware alignment of reads to the genome. Cell Ranger then uses the transcript annotation GTF to bucket the reads into exonic  intronic  and intergenic  and by whether the reads align confidently to the genome. A read is exonic if at least 50% of it intersects an exon  intronic if it is non exonic and intersects an intron  and intergenic otherwise. For reads that align to a single exonic locus but also align to 1 or more non exonic loci  the exonic locus is prioritized and the read is considered to be confidently mapped to the exonic locus with MAPQ 255. Cell Ranger further aligns exonic reads to annotated transcripts  looking for compatibility. A read that is compatible with the exons of an annotated transcript  and aligned to the same strand  is considered mapped to the transcriptome. If the read is compatible with a single gene annotation  it is considered uniquely confidently mapped to the transcriptome. Only reads that  are confidently mapped to the transcriptome are used for UMI counting. Cell Ranger takes as input the expected number of recovered cells  N see    expect cells. Let m be a robust estimate of the maximum total UMI counts  taken as the 99th percentile of the top N barcodes by total UMI counts. All barcodes whose total UMI counts exceed m/10 are called as cells. This is performed separately for each GEM group library and  if the reference contains multiple genomes  for each genome. Genome build: Danio rerio Ensemble 91 Supplementary files format and content: gene barcode expression matrix", "liver cells", "Exposure solutions were prepared by adding 100\u03bcg/L arsenic  300\u03bcg/L DCAcAm or both of them to culture water. The exposure solution were was replaced every 2 days.  post 23 d exposure  zebrafish were collected and liver were rapidly extracted on ice.", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell 3\u2019 Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer\u2019s protocol. Libraries were sequenced on an Illumina Hiseq PE150.", null, "tissue:liver single cell suspension|age:16 wpf|exposed pollutants:300ug/L DCAcAm", "GSM4558082", "GSM4558082: Dc300; Danio rerio; RNA Seq", "GSM4558082", null, "1", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell three prime Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer's protocol. Libraries were sequenced on an Illumina Hiseq PE150.", "GEO Accession:GSM4558082", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP262133", null, null, "Dc300_1.fq.gz Dc300_2.fq.gz", "fastq fastq", 127027640400.0, 423425468.0, "GSM4558082 r1", "0:150 1:150", "A:30842125524;C:23778726057;G:39107636584;T:33274935260;N:24216975", 150, 150, null, null, 30842125524, 23778726057, 39107636584, 33274935260, 24216975, "SRX8357869", "SRS6673975", "SRA1076689", "GEO", "Nanjing University", 2, 0.0, 0.91236, 0.0, 0.02333, 1.0, 0.90879, null, 0.42849, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2020-05-18", "Adult", "Adult", "Liver", "Liver and Biliary System"], [59290, "SRR11806490", "SRX8357868", "SRS6673977", "SRP262133", "PRJNA633496", "Single cell sequencing reveals heterogeneity effects of arsenic or/and 2 2 dichloroacetamide on zebrafish liver", "GSE150751", "Transcriptome Analysis", "Arsenic and DBPs has been found to be one of the major risk in many regions of the world. However  current understanding of thier combined toxicities are unclear. Here we used single cell RNA sequencing to provide the transcriptome heterogeneity of 13563 liver cells obtained from zebrafishes exposed to 100\u00b5g/L arsenic  300\u00b5g/L dichloroacetanilide DCAcAm and co exposure for 23 days. Five liver cell populations were identified. We found that the hepatocytes and macrophages were the main target of arsenic and DCAcAm exposure. And the hepatocytes of male and female showed a huge difference  when expsoure to arsenic and DCAcAm. Overall design: Single cell RNA sequencing were adopted to learn the transcriptional variation in zebrafish liver exposure to arsenic and DCAcAm.", null, null, null, "As100", "GSM4558081", null, "source name:liver cells|tissue:liver single cell suspension|age:16 wpf|exposed pollutants:100ug/L arsenic", "As100", "We use FastQC to perform basic statistics on the quality of the raw reads. Then  those read sequences produced by the Illumina pipeline in FASTQ format were pre processed through Trimmomatic software which can be summarized as below:1 Remove low quality reads: scan the read with a 4 base wide sliding window  cutting when the average quality per base drops below 10 SLIDINGWINDOW:  4:10 2 Remove trailing low quality or N bases below quality 3 TRAILING:3 3 Remove adapters : there are two modes to remove the adapter sequence: a.  alignment with the adapter sequence  the number of matching bases were greater than 7 and mismatch=2; b.when read1 and read2 overlapping base scoring  greater than 30  removed non overlapping portions ILLUMINACLIP: adapter.fa:  2: 30: 7 4 Drop reads below the 26 bases long 5 Discard those reads that can not form paired The remaining reads that passed all the filtering steps was counted as clean reads and all subsequent analyses were based on this. At last  we use FastQC to perform basic statistics on the quality of the clean reads. Cell Ranger uses an aligner called STAR  which peforms splicing aware alignment of reads to the genome. Cell Ranger then uses the transcript annotation GTF to bucket the reads into exonic  intronic  and intergenic  and by whether the reads align confidently to the genome. A read is exonic if at least 50% of it intersects an exon  intronic if it is non exonic and intersects an intron  and intergenic otherwise. For reads that align to a single exonic locus but also align to 1 or more non exonic loci  the exonic locus is prioritized and the read is considered to be confidently mapped to the exonic locus with MAPQ 255. Cell Ranger further aligns exonic reads to annotated transcripts  looking for compatibility. A read that is compatible with the exons of an annotated transcript  and aligned to the same strand  is considered mapped to the transcriptome. If the read is compatible with a single gene annotation  it is considered uniquely confidently mapped to the transcriptome. Only reads that  are confidently mapped to the transcriptome are used for UMI counting. Cell Ranger takes as input the expected number of recovered cells  N see    expect cells. Let m be a robust estimate of the maximum total UMI counts  taken as the 99th percentile of the top N barcodes by total UMI counts. All barcodes whose total UMI counts exceed m/10 are called as cells. This is performed separately for each GEM group library and  if the reference contains multiple genomes  for each genome. Genome build: Danio rerio Ensemble 91 Supplementary files format and content: gene barcode expression matrix", "liver cells", "Exposure solutions were prepared by adding 100\u03bcg/L arsenic  300\u03bcg/L DCAcAm or both of them to culture water. The exposure solution were was replaced every 2 days.  post 23 d exposure  zebrafish were collected and liver were rapidly extracted on ice.", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell 3\u2019 Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer\u2019s protocol. Libraries were sequenced on an Illumina Hiseq PE150.", null, "tissue:liver single cell suspension|age:16 wpf|exposed pollutants:100ug/L arsenic", "GSM4558081", "GSM4558081: As100; Danio rerio; RNA Seq", "GSM4558081", null, "1", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell three prime Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer's protocol. Libraries were sequenced on an Illumina Hiseq PE150.", "GEO Accession:GSM4558081", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP262133", null, null, "As100_2.fq.gz As100_1.fq.gz", "fastq fastq", 102837948900.0, 342793163.0, "GSM4558081 r1", "0:150 1:150", "A:24894384372;C:19593836618;G:31314101265;T:27014778377;N:20848268", 150, 150, null, null, 24894384372, 19593836618, 31314101265, 27014778377, 20848268, "SRX8357868", "SRS6673977", "SRA1076689", "GEO", "Nanjing University", 2, 0.0, 0.91738, 0.0, 0.02836, 1.0, 0.89536, null, 0.46528, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2020-05-18", "Adult", "Adult", "Liver", "Liver and Biliary System"], [59291, "SRR11806489", "SRX8357867", "SRS6673974", "SRP262133", "PRJNA633496", "Single cell sequencing reveals heterogeneity effects of arsenic or/and 2 2 dichloroacetamide on zebrafish liver", "GSE150751", "Transcriptome Analysis", "Arsenic and DBPs has been found to be one of the major risk in many regions of the world. However  current understanding of thier combined toxicities are unclear. Here we used single cell RNA sequencing to provide the transcriptome heterogeneity of 13563 liver cells obtained from zebrafishes exposed to 100\u00b5g/L arsenic  300\u00b5g/L dichloroacetanilide DCAcAm and co exposure for 23 days. Five liver cell populations were identified. We found that the hepatocytes and macrophages were the main target of arsenic and DCAcAm exposure. And the hepatocytes of male and female showed a huge difference  when expsoure to arsenic and DCAcAm. Overall design: Single cell RNA sequencing were adopted to learn the transcriptional variation in zebrafish liver exposure to arsenic and DCAcAm.", null, null, null, "CK", "GSM4558080", null, "source name:liver cells|tissue:liver single cell suspension|age:16 wpf|exposed pollutants:n1", "CK", "We use FastQC to perform basic statistics on the quality of the raw reads. Then  those read sequences produced by the Illumina pipeline in FASTQ format were pre processed through Trimmomatic software which can be summarized as below:1 Remove low quality reads: scan the read with a 4 base wide sliding window  cutting when the average quality per base drops below 10 SLIDINGWINDOW:  4:10 2 Remove trailing low quality or N bases below quality 3 TRAILING:3 3 Remove adapters : there are two modes to remove the adapter sequence: a.  alignment with the adapter sequence  the number of matching bases were greater than 7 and mismatch=2; b.when read1 and read2 overlapping base scoring  greater than 30  removed non overlapping portions ILLUMINACLIP: adapter.fa:  2: 30: 7 4 Drop reads below the 26 bases long 5 Discard those reads that can not form paired The remaining reads that passed all the filtering steps was counted as clean reads and all subsequent analyses were based on this. At last  we use FastQC to perform basic statistics on the quality of the clean reads. Cell Ranger uses an aligner called STAR  which peforms splicing aware alignment of reads to the genome. Cell Ranger then uses the transcript annotation GTF to bucket the reads into exonic  intronic  and intergenic  and by whether the reads align confidently to the genome. A read is exonic if at least 50% of it intersects an exon  intronic if it is non exonic and intersects an intron  and intergenic otherwise. For reads that align to a single exonic locus but also align to 1 or more non exonic loci  the exonic locus is prioritized and the read is considered to be confidently mapped to the exonic locus with MAPQ 255. Cell Ranger further aligns exonic reads to annotated transcripts  looking for compatibility. A read that is compatible with the exons of an annotated transcript  and aligned to the same strand  is considered mapped to the transcriptome. If the read is compatible with a single gene annotation  it is considered uniquely confidently mapped to the transcriptome. Only reads that  are confidently mapped to the transcriptome are used for UMI counting. Cell Ranger takes as input the expected number of recovered cells  N see    expect cells. Let m be a robust estimate of the maximum total UMI counts  taken as the 99th percentile of the top N barcodes by total UMI counts. All barcodes whose total UMI counts exceed m/10 are called as cells. This is performed separately for each GEM group library and  if the reference contains multiple genomes  for each genome. Genome build: Danio rerio Ensemble 91 Supplementary files format and content: gene barcode expression matrix", "liver cells", "Exposure solutions were prepared by adding 100\u03bcg/L arsenic  300\u03bcg/L DCAcAm or both of them to culture water. The exposure solution were was replaced every 2 days.  post 23 d exposure  zebrafish were collected and liver were rapidly extracted on ice.", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell 3\u2019 Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer\u2019s protocol. Libraries were sequenced on an Illumina Hiseq PE150.", null, "tissue:liver single cell suspension|age:16 wpf|exposed pollutants:n1", "GSM4558080", "GSM4558080: CK; Danio rerio; RNA Seq", "GSM4558080", null, "1", "The isolated liver tissue was digested into  cell suspension with dispase. Cells were loaded on a GemCode Single Cell Instrument10x Genomics  USA to generate single cell Gel bead in Emulsion GEMs. ScRNA seq libraries were prepared using the GemCode Single Cell three prime Gel Bead  Chip and Library Kits 10x Genomics  USA as per the manufacturer's protocol. Libraries were sequenced on an Illumina Hiseq PE150.", "GEO Accession:GSM4558080", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina NovaSeq 6000", null, "SRP262133", null, null, "CK_1.fq.gz CK_2.fq.gz", "fastq fastq", 133916231400.0, 446387438.0, "GSM4558080 r1", "0:150 1:150", "A:32477145943;C:25399997371;G:40326238358;T:35690408393;N:22441335", 150, 150, null, null, 32477145943, 25399997371, 40326238358, 35690408393, 22441335, "SRX8357867", "SRS6673974", "SRA1076689", "GEO", "Nanjing University", 2, 0.0, 0.91836, 0.0, 0.02382, 1.0, 0.90871, null, 0.46105, 150, 150, "T", "B", "mate1 technical by mapping diff", "illumina", "novaseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "China", "2020-05-18", "Adult", "Adult", "Liver", "Liver and Biliary System"], [65633, "SRR15427704", "SRX11729087", "SRS9757823", "SRP332278", "PRJNA754150", "Single cell transcriptomic profiling of healthy and fibrotic adult zebrafish liver reveals conserved cell identities and pathways with human liver", "GSE181987", "Other", "Liver fibrosis is the excessive accumulation of extracellular matrix that can progress to cirrhosis and failure if untreated. The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "MPI MT 3", "GSM5515736", null, "source name:Adult zebrafish liver dissection|genotype:mpi+/  mss7|tissue:Liver", "MPI MT 3", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:mpi+/  mss7|tissue:Liver", "GSM5515736", "GSM5515736: MPI MT 3; Danio rerio; RNA Seq", "GSM5515736", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "GEO Accession:GSM5515736", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP332278", null, "loader:fastq load.py|options:  platform=Illumina   readTypes=TTB   read1PairFiles=JACH01 MT5 0 G S8 L001 I1 001.fastq.gz   read2PairFiles=JACH01 MT5 0 G S8 L001 R1 001.fastq.gz   read3PairFiles=JACH01 MT5 0 G S8 L001 R2 001.fastq.gz", "JACH01_MT5_0_G_S8_L001_I1_001.fastq.gz JACH01_MT5_0_G_S8_L001_R1_001.fastq.gz JACH01_MT5_0_G_S8_L001_R2_001.fastq.gz", "fastq fastq fastq", 12954775700.0, 129547757.0, "GSM5515736 r1", "0:8 1:30 2:62", "A:2373305749;C:1813473007;G:1779922398;T:2065049504;N:210276", 8, 30, 62, null, 2373305749, 1813473007, 1779922398, 2065049504, 210276, "SRX11729087", "SRS9757823", "SRA1277309", "GEO", "Jaime Chu Lab, Pediatrics, Icahn School of Medicine at Mount Sinai", 1, 0.94564, null, 0.06912, null, 0.88712, null, 0.74857, null, 62, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-08-12", "Adult", "Adult", "Liver", "Liver and Biliary System"], [65634, "SRR15427705", "SRX11729087", "SRS9757823", "SRP332278", "PRJNA754150", "Single cell transcriptomic profiling of healthy and fibrotic adult zebrafish liver reveals conserved cell identities and pathways with human liver", "GSE181987", "Other", "Liver fibrosis is the excessive accumulation of extracellular matrix that can progress to cirrhosis and failure if untreated. The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "MPI MT 3", "GSM5515736", null, "source name:Adult zebrafish liver dissection|genotype:mpi+/  mss7|tissue:Liver", "MPI MT 3", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:mpi+/  mss7|tissue:Liver", "GSM5515736", "GSM5515736: MPI MT 3; Danio rerio; RNA Seq", "GSM5515736", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "MPI MT 2", "GSM5515735", null, "source name:Adult zebrafish liver dissection|genotype:mpi+/  mss7|tissue:Liver", "MPI MT 2", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:mpi+/  mss7|tissue:Liver", "GSM5515735", "GSM5515735: MPI MT 2; Danio rerio; RNA Seq", "GSM5515735", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "MPI MT 2", "GSM5515735", null, "source name:Adult zebrafish liver dissection|genotype:mpi+/  mss7|tissue:Liver", "MPI MT 2", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:mpi+/  mss7|tissue:Liver", "GSM5515735", "GSM5515735: MPI MT 2; Danio rerio; RNA Seq", "GSM5515735", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "MPI MT 1", "GSM5515734", null, "source name:Adult zebrafish liver dissection|genotype:mpi+/  mss7|tissue:Liver", "MPI MT 1", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:mpi+/  mss7|tissue:Liver", "GSM5515734", "GSM5515734: MPI MT 1; Danio rerio; RNA Seq", "GSM5515734", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "MPI MT 1", "GSM5515734", null, "source name:Adult zebrafish liver dissection|genotype:mpi+/  mss7|tissue:Liver", "MPI MT 1", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:mpi+/  mss7|tissue:Liver", "GSM5515734", "GSM5515734: MPI MT 1; Danio rerio; RNA Seq", "GSM5515734", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "WT 3", "GSM5515733", null, "source name:Adult zebrafish liver dissection|genotype:WT|tissue:Liver", "WT 3", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:WT|tissue:Liver", "GSM5515733", "GSM5515733: WT 3; Danio rerio; RNA Seq", "GSM5515733", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "WT 3", "GSM5515733", null, "source name:Adult zebrafish liver dissection|genotype:WT|tissue:Liver", "WT 3", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:WT|tissue:Liver", "GSM5515733", "GSM5515733: WT 3; Danio rerio; RNA Seq", "GSM5515733", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "WT 2", "GSM5515732", null, "source name:Adult zebrafish liver dissection|genotype:WT|tissue:Liver", "WT 2", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:WT|tissue:Liver", "GSM5515732", "GSM5515732: WT 2; Danio rerio; RNA Seq", "GSM5515732", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "WT 2", "GSM5515732", null, "source name:Adult zebrafish liver dissection|genotype:WT|tissue:Liver", "WT 2", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:WT|tissue:Liver", "GSM5515732", "GSM5515732: WT 2; Danio rerio; RNA Seq", "GSM5515732", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "WT 1", "GSM5515731", null, "source name:Adult zebrafish liver dissection|genotype:WT|tissue:Liver", "WT 1", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:WT|tissue:Liver", "GSM5515731", "GSM5515731: WT 1; Danio rerio; RNA Seq", "GSM5515731", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. 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The mechanisms of fibrogenesis are multi faceted and remain elusive with no approved antifibrotic treatments available. Here we use single cell RNA sequencing scRNA seq of the adult zebrafish liver to study the molecular and cellular dynamics of the liver at a single cell level and demonstrate the value of the adult zebrafish as a model for studying liver fibrosis. scRNA seq reveals transcriptionally unique populations of hepatic cell types that comprise the zebrafish liver. Joint clustering with human liver scRNA seq data demonstrates high conservation of transcriptional profiles and human marker genes in zebrafish cell types. Human and zebrafish hepatic stellate cells HSCs  the driver cell in liver fibrosis  specifically show conservation of transcriptional profiles and we uncover Colec11 as a novel  conserved marker for zebrafish HSCs. To demonstrate the power of scRNA seq to study liver fibrosis  we performed scRNA seq on our zebrafish model of a pediatric liver disease with characteristic early  progressive liver fibrosis caused by mutation in mannose phosphate isomerase MPI. Comparison of differentially expressed genes from human and zebrafish MPI mutant HSC datasets demonstrated similar activation of fibrosis signaling pathways and upstream regulators. CellPhoneDB analysis revealed important receptor ligand interactions within normal and fibrotic states. This study establishes the first scRNA seq atlas of the adult zebrafish liver  highlights the high degree of similarity to the human liver  and strengthens its value as a model to study liver fibrosis. Overall design: Single cell RNA sequencing analysis of adult zebrafish liver tissue from mpi+/  mss7 and WT siblings Please note that the Series supplementary files were generated from multiple samples as following: zf WT MPIMT EC HSC subset   GSM5515731 GSM5515736 zf WT MPIMT liver   GSM5515731 GSM5515736 zf liver atlas   GSM5515731 GSM5515733 joint fish human   GSM5515731 GSM5515733 as well as data from GSE115469 samples GSM317872 317876. and the description of each file is provided in the readme.txt.", null, "pubmed:35315595", null, "WT 1", "GSM5515731", null, "source name:Adult zebrafish liver dissection|genotype:WT|tissue:Liver", "WT 1", "FASTQ were demultiplexed using Cell Ranger v2.0 and aligned to the Grcz11 zebrafish Cell barcodes and unique molecular identifiers UMIs were extracted and \u201cRaw\u201d UMI matrix generated for each sample extracted cell barcodes associated with at least 150 UMIs from the \u201cRaw\u201d output UMI matrices of CellRanger Genome build: danRer11", "Adult zebrafish liver dissection", null, "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "Adult fish were maintained on a 14:10 light/dark cycle at 28\u00b0C.", "genotype:WT|tissue:Liver", "GSM5515731", "GSM5515731: WT 1; Danio rerio; RNA Seq", "GSM5515731", null, "1", "Livers were dissected from 18 mpf adult zebrafish. Single cell suspensions were generated as described in Materials and Methods. Cells were dissociated and digested using standard collagenase and DNAse protocols  and single cell suspensions were filtered through a 70um filter. Suspensions were loaded into 10X Chromium gel beads. Library construction was performed as per 10X Genomics v3 chemistry kit. 10X chromium", "GEO Accession:GSM5515731", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "NextSeq 500", null, "SRP332278", null, "loader:fastq load.py|options:  platform=Illumina   readTypes=TTB   read1PairFiles=JACH01 WT2 0 G S3 L002 I1 001.fastq.gz   read2PairFiles=JACH01 WT2 0 G S3 L002 R1 001.fastq.gz   read3PairFiles=JACH01 WT2 0 G S3 L002 R2 001.fastq.gz", "JACH01_WT2_0_G_S3_L002_I1_001.fastq.gz JACH01_WT2_0_G_S3_L002_R1_001.fastq.gz JACH01_WT2_0_G_S3_L002_R2_001.fastq.gz", "fastq fastq fastq", 14981913300.0, 149819133.0, "GSM5515731 r2", "0:8 1:30 2:62", "A:2757221756;C:2158264290;G:2042268570;T:2330874969;N:156661", 8, 30, 62, null, 2757221756, 2158264290, 2042268570, 2330874969, 156661, "SRX11729082", "SRS9757819", "SRA1277309", "GEO", "Jaime Chu Lab, Pediatrics, Icahn School of Medicine at Mount Sinai", 1, 0.94701, null, 0.05368, null, 0.89591, null, 0.57205, null, 62, null, "B", null, "usable mapping rate", "illumina", "nextseq", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "United States", "2021-08-12", "Adult", "Adult", "Liver", "Liver and Biliary System"], [67832, "SRR17375072", "SRX13549231", "SRS11443005", "SRP352824", "PRJNA793009", "Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches single cells", "GSE192740", "Other", "Analysis of CITE seq data   Nuclei RNA seq data and single cell RNA seq data on CD45+ and CD45  cells isolated from the livers of mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar  from healthy and steatotic human livers  from hamster liver  pig liver  chicken liver  monkey liver and zebrafish liver. We also performed Spatial Transcriptomics analysis on heatlhy mouse livers  NAFLD mouse livers  healthy human livers and steatotic human livers. Overall design: Single cell RNA Seq = Liver CD45+ and CD45  cells derived from mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar. Liver CD45+ and CD45  cells derived from healthy and obese humans. 10 Visium Spatial Seq = mouse StSt liver  mouse StSt capsule  mouse NAFLD liver   human non steatotic liver  human steatotic liver", "parent bioproject:PRJNA793005", "pubmed:35021063;pubmed:36304458", null, "Zebrafish 002 Whole Liver Cells Zebrafish", "GSM5764413", null, "tissue:Liver|shortfilename:CS131|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:1241", "Zebrafish 002 Whole Liver Cells Zebrafish", "Raw data bcl files were first demultiplexed using Cell Ranger mkfastq version 3.1.0 or version 3.0.2 Demultiplexed data was then processed using the Cell Ranger count pipeline version 3.1.0 or version 3.0.2. Cite seq samples were mapped against the TotalSeqA whitelist. Genome build: mm10 Mouse  hg19 Human  GRCz10 Zebrafish  MesAur1.0.100 Hamster  GRCg6a.96 Chicken  Sscrofa11.1.96 Pig or Macaca facicularis 5.0.100 Macaque Supplementary files format and content: h5 or txt files including raw gene \u2013 and if present \u2013 antibody counts output CellRanger Count Supplementary files format and content: rds file: Seurat object", "Liver", null, "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", null, "shortfilename:CS131|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:1241", "GSM5764413", "GSM5764413: Zebrafish 002 Whole Liver Cells Zebrafish; Danio rerio; RNA Seq", "GSM5764413", null, "1", "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. 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We also performed Spatial Transcriptomics analysis on heatlhy mouse livers  NAFLD mouse livers  healthy human livers and steatotic human livers. Overall design: Single cell RNA Seq = Liver CD45+ and CD45  cells derived from mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar. Liver CD45+ and CD45  cells derived from healthy and obese humans. 10 Visium Spatial Seq = mouse StSt liver  mouse StSt capsule  mouse NAFLD liver   human non steatotic liver  human steatotic liver", "parent bioproject:PRJNA793005", "pubmed:35021063;pubmed:36304458", null, "Zebrafish 001 Whole Liver Cells Zebrafish", "GSM5764412", null, "tissue:Liver|shortfilename:CS130|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:2256", "Zebrafish 001 Whole Liver Cells Zebrafish", "Raw data bcl files were first demultiplexed using Cell Ranger mkfastq version 3.1.0 or version 3.0.2 Demultiplexed data was then processed using the Cell Ranger count pipeline version 3.1.0 or version 3.0.2. Cite seq samples were mapped against the TotalSeqA whitelist. Genome build: mm10 Mouse  hg19 Human  GRCz10 Zebrafish  MesAur1.0.100 Hamster  GRCg6a.96 Chicken  Sscrofa11.1.96 Pig or Macaca facicularis 5.0.100 Macaque Supplementary files format and content: h5 or txt files including raw gene \u2013 and if present \u2013 antibody counts output CellRanger Count Supplementary files format and content: rds file: Seurat object", "Liver", null, "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", null, "shortfilename:CS130|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:2256", "GSM5764412", "GSM5764412: Zebrafish 001 Whole Liver Cells Zebrafish; Danio rerio; RNA Seq", "GSM5764412", null, "1", "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", "GEO Accession:GSM5764412", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP352824", null, null, "CS130_R1.fastq.gz CS130_R2.fastq.gz", "fastq fastq", 29028764681.0, 243939199.0, "GSM5764412 r1", "0:28 1:91", "A:7990080958;C:6832189305;G:6802247428;T:7395232074;N:9014916", 28, 91, null, null, 7990080958, 6832189305, 6802247428, 7395232074, 9014916, "SRX13549230", "SRS11443004", "SRA1349905", "GEO", "VIB Inflammation Research Center, VIB-University of Ghent", 2, 0.00621, 0.93648, 0.00152, 0.07051, 0.99466, 0.85036, 0.33907, 0.45636, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Belgium", "2021-12-29", "Undetermined", "Undetermined", "Liver", "Liver and Biliary System"], [67834, "SRR17375070", "SRX13549229", "SRS11443003", "SRP352824", "PRJNA793009", "Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches single cells", "GSE192740", "Other", "Analysis of CITE seq data   Nuclei RNA seq data and single cell RNA seq data on CD45+ and CD45  cells isolated from the livers of mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar  from healthy and steatotic human livers  from hamster liver  pig liver  chicken liver  monkey liver and zebrafish liver. We also performed Spatial Transcriptomics analysis on heatlhy mouse livers  NAFLD mouse livers  healthy human livers and steatotic human livers. Overall design: Single cell RNA Seq = Liver CD45+ and CD45  cells derived from mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar. Liver CD45+ and CD45  cells derived from healthy and obese humans. 10 Visium Spatial Seq = mouse StSt liver  mouse StSt capsule  mouse NAFLD liver   human non steatotic liver  human steatotic liver", "parent bioproject:PRJNA793005", "pubmed:35021063;pubmed:36304458", null, "Zebrafish 002 Liver mpeg1.1+ cells Zebrafish", "GSM5764411", null, "tissue:Liver|shortfilename:CS129|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:4126", "Zebrafish 002 Liver mpeg1.1+ cells Zebrafish", "Raw data bcl files were first demultiplexed using Cell Ranger mkfastq version 3.1.0 or version 3.0.2 Demultiplexed data was then processed using the Cell Ranger count pipeline version 3.1.0 or version 3.0.2. Cite seq samples were mapped against the TotalSeqA whitelist. Genome build: mm10 Mouse  hg19 Human  GRCz10 Zebrafish  MesAur1.0.100 Hamster  GRCg6a.96 Chicken  Sscrofa11.1.96 Pig or Macaca facicularis 5.0.100 Macaque Supplementary files format and content: h5 or txt files including raw gene \u2013 and if present \u2013 antibody counts output CellRanger Count Supplementary files format and content: rds file: Seurat object", "Liver", null, "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", null, "shortfilename:CS129|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:4126", "GSM5764411", "GSM5764411: Zebrafish 002 Liver mpeg1.1+ cells Zebrafish; Danio rerio; RNA Seq", "GSM5764411", null, "1", "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", "GEO Accession:GSM5764411", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP352824", null, null, "CS129_R1.fastq.gz CS129_R2.fastq.gz", "fastq fastq", 37123150869.0, 311959251.0, "GSM5764411 r1", "0:28 1:91", "A:10576275333;C:7976755033;G:8122940005;T:10435522767;N:11657731", 28, 91, null, null, 10576275333, 7976755033, 8122940005, 10435522767, 11657731, "SRX13549229", "SRS11443003", "SRA1349905", "GEO", "VIB Inflammation Research Center, VIB-University of Ghent", 2, 0.00585, 0.89093, 0.00199, 0.20548, 0.99269, 0.82597, 0.42801, 0.61509, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Belgium", "2021-12-29", "Undetermined", "Undetermined", "Liver", "Liver and Biliary System"], [67835, "SRR17375069", "SRX13549228", "SRS11443002", "SRP352824", "PRJNA793009", "Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches single cells", "GSE192740", "Other", "Analysis of CITE seq data   Nuclei RNA seq data and single cell RNA seq data on CD45+ and CD45  cells isolated from the livers of mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar  from healthy and steatotic human livers  from hamster liver  pig liver  chicken liver  monkey liver and zebrafish liver. We also performed Spatial Transcriptomics analysis on heatlhy mouse livers  NAFLD mouse livers  healthy human livers and steatotic human livers. Overall design: Single cell RNA Seq = Liver CD45+ and CD45  cells derived from mice fed a standard diet SD or western diet WD; fat  cholesterol and sugar. Liver CD45+ and CD45  cells derived from healthy and obese humans. 10 Visium Spatial Seq = mouse StSt liver  mouse StSt capsule  mouse NAFLD liver   human non steatotic liver  human steatotic liver", "parent bioproject:PRJNA793005", "pubmed:35021063;pubmed:36304458", null, "Zebrafish 001 Liver mpeg1.1+ cells Zebrafish", "GSM5764410", null, "tissue:Liver|shortfilename:CS128|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:1229", "Zebrafish 001 Liver mpeg1.1+ cells Zebrafish", "Raw data bcl files were first demultiplexed using Cell Ranger mkfastq version 3.1.0 or version 3.0.2 Demultiplexed data was then processed using the Cell Ranger count pipeline version 3.1.0 or version 3.0.2. Cite seq samples were mapped against the TotalSeqA whitelist. Genome build: mm10 Mouse  hg19 Human  GRCz10 Zebrafish  MesAur1.0.100 Hamster  GRCg6a.96 Chicken  Sscrofa11.1.96 Pig or Macaca facicularis 5.0.100 Macaque Supplementary files format and content: h5 or txt files including raw gene \u2013 and if present \u2013 antibody counts output CellRanger Count Supplementary files format and content: rds file: Seurat object", "Liver", null, "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", null, "shortfilename:CS128|strain:Tgmpeg1:EGFPgl22|platform:10x Genomics \u2013 v3|digestion method:Ex Vivo|number of added abs:0|number of cells:1229", "GSM5764410", "GSM5764410: Zebrafish 001 Liver mpeg1.1+ cells Zebrafish; Danio rerio; RNA Seq", "GSM5764410", null, "1", "All Methods listed in Guilliams et al. Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches. Cell. 2022.", "GEO Accession:GSM5764410", "RNA-Seq", "TRANSCRIPTOMIC", "cDNA", "PAIRED", "ILLUMINA", "Illumina HiSeq 4000", null, "SRP352824", null, null, "CS128_R1.fastq.gz CS128_R2.fastq.gz", "fastq fastq", 38316694094.0, 321989026.0, "GSM5764410 r1", "0:28 1:91", "A:10814226120;C:8293271134;G:8575797871;T:10621330197;N:12068772", 28, 91, null, null, 10814226120, 8293271134, 8575797871, 10621330197, 12068772, "SRX13549228", "SRS11443002", "SRA1349905", "GEO", "VIB Inflammation Research Center, VIB-University of Ghent", 2, 0.00626, 0.88237, 0.00215, 0.18876, 0.99249, 0.83049, 0.41451, 0.59559, 28, 91, "T", "B", "sc-like readlen", "illumina", "hiseq_era", "unknown", "cdna_unspecified", "unknown", "sc", "single_cell_droplet", "10x", null, "Belgium", "2021-12-29", "Undetermined", "Undetermined", "Liver", "Liver and Biliary System"]], "truncated": false, "filtered_table_rows_count": 23, "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], 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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": "Liver"}}, "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=Liver", "results": [{"value": "RNA-Seq", "label": "RNA-Seq", "count": 23, "toggle_url": "http://metadata.rnaquarium.org/metadata/run_metadata.json?experiment.library_source=TRANSCRIPTOMIC&technology=10x&tissue_curation=Liver&experiment.library_strategy=RNA-Seq", "selected": false}], "truncated": false}, "experiment.library_source": {"name": 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