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Status |
Public on Jul 05, 2024 |
Title |
Donor 3 medulla |
Sample type |
SRA |
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Source name |
Kidney medulla
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Organism |
Homo sapiens |
Characteristics |
tissue: Kidney medulla
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Extracted molecule |
genomic DNA |
Extraction protocol |
Nuclei were isolated from 2g of kidney cortex or medulla, homogenized in nuclei isolation buffer (250mM sucrose, 10mM Tris pH 7.5, 3mM MgCl2, 0.1% NP40) by gentleMacs using dissociator proram E.01 and filtered through a 200uM filter. Homogenate was resuspended in 1ml of ATAC-Resuspension Buffer with detergents (10mM Tris pH 7.5, 10mM NaCl, 3mM MgCl2, 100ug/mL digitonin, 0.1% Tween, 0.1% NP40) for 3 minutes on ice and then detergents were diluted by resuspending with 14mL ATAC-Resuspension Buffer with tween alone (10mM Tris pH 7.5, 10mM NaCl, 3mM MgCl2, 0.1% Tween). Nuclei were passed through a 40mm filter, counted, and 15,000 nuclei were used for transposition and library generation using the Chromium Next GEM Single Cell ATAC Library & Gel Bead Kit v1.1 (10x Genomics, 1000176). Chromium Next GEM Single Cell ATAC Library & Gel Bead Kit v1.1 with 15,000 nuclei according the manufacturer's protocol.
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Library strategy |
ATAC-seq |
Library source |
genomic single cell |
Library selection |
other |
Instrument model |
Illumina NovaSeq 6000 |
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Description |
single cell ATAC-sequencing
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Data processing |
Demultiplexing, read alignment, and cell calling was performed with the Cell Ranger ATAC Pipeline (v1.2, using hg38) to generate scATAC fragment files and peak barcode matrices. Fragment files were loaded into R (3.6.1) using the createArrowFiles function in ArchR (v.0.9.5)111. TSS enrichment and number of unique fragments calculated on a per-cell basis were used to remove low quality cells, cutoffs were defined for each library (TSS enrichment >6-7, unique fragments <4000-6800). Dimensionality reduction, batch effect correction, clustering, integration with kidney scRNA-seq data (PMID: 31506348), and cluster-specific 500bp fixed-width peak calling were performed using the addIterativeLSI, addHarmony, addClusters, addGeneIntegrationMatrix, addGroupCoverages, and addReproduciblePeakSet functions in ArchR. Gene activity scores were calculated using the ArchR function getMarkerFeatures. Motif enrichment within cell type-specific peaks were identified using the addMotifAnnotations and peakAnnoEnrichment functions and Homo sapiens motifs from CIS-BP. Bed files for the fragments from each cell type from all three donors were generated by using cellids from ArchR to extract cell type specific fragments from fragment files. Cell type-specific bigwig files were generated from these bed files using MACS2 callpeak with options: -f BED -g 2.7e9 --keep-dup all -B --SPMR --shift -75 --extsize 150 -q 0.05 --nomodel --nolambda. To identify clusters of cell type-specific peaks, the cell type-by-peak matrix was normalized, log transformed, and k-means clustered with 12 clusters. Two clusters corresponded to ubiquitously accessible peaks were combined for a total of 11 clusters. Assembly: hg38 Supplementary files format and content: Peak barcode matrices were generated using the Cell Ranger ATAC Pipeline (v1.2, using hg38 genome assembly)
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Submission date |
Apr 01, 2024 |
Last update date |
Aug 08, 2024 |
Contact name |
Gabriel Loeb |
E-mail(s) |
gabriel.loeb@ucsf.edu
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Organization name |
UCSF
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Department |
Medicine
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Street address |
555 Mission Bay Blvd South, Rm 382H
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City |
San Francisco |
State/province |
CA |
ZIP/Postal code |
94143 |
Country |
USA |
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Platform ID |
GPL24676 |
Series (1) |
GSE262931 |
Variants in tubule epithelial regulatory elements mediate most heritable differences in human kidney function |
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Relations |
BioSample |
SAMN40709745 |
SRA |
SRX24119190 |
Supplementary file |
Size |
Download |
File type/resource |
GSM8181668_Donor3_medulla_filtered_peak_bc_matrix.h5 |
193.3 Mb |
(ftp)(http) |
H5 |
GSM8181668_Donor3_medulla_fragments.tsv.gz |
4.4 Gb |
(ftp)(http) |
TSV |
GSM8181668_Donor3_medulla_fragments.tsv.gz.tbi.gz |
1.5 Mb |
(ftp)(http) |
TBI |
SRA Run Selector |
Raw data are available in SRA |
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