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| Status |
Public on May 28, 2021 |
| Title |
NC_PBMC_scATAC-seq |
| Sample type |
SRA |
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| Source name |
Peripheral blood mononuclear cells (PBMCs)
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| Organism |
Homo sapiens |
| Characteristics |
disease state: Healthy controls
tissue: peripheral blood
cell type: Peripheral blood mononuclear cells (PBMCs)
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
PBMCs were separated using an equal proportion of Ficoll-Paque Plus. Nuclei suspensions were obtained by adding lysis buffer (10 mM Tris-HCl, 3 mM MgCl2, 10 mM NaCl , 0.1% Tween-20, 0.1% Nonidet P40 Substitute, 1% BSA). The final libraries were constructed via PCR with P5 and P7 primers in Illumina® bridge amplification.
scATAC-seq libraries were generated according to the Chromium Single Cell ATAC protocol (10x GENOMICS)
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| Library strategy |
ATAC-seq |
| Library source |
genomic |
| Library selection |
other |
| Instrument model |
BGISEQ-500 |
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| Description |
J1901331_S1_L001
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| Data processing |
Barcode processing: To improve data quality, a ‘whitelist’ of correct barcode sequences was applied to fix the occasional sequencing error in barcodes obtained from the ‘I2’ index read
Genome alignment: Reference-based analysis was performed using the Cell Ranger ATAC pipeline. BWA-MEM was applied with default parameters to align the trimmed read pairs that were greater than 25 bp to GRCh38
Filteing: We filtered scATAC-seq data using cut-offs of 1,000 unique nuclear fragments per cell and a transcription start site (TSS) enrichment score of 8 to exclude low-quality cells in 10x genomic Cell Ranger ATAC platform
Peak calling: First, the number of transposition events at each base pair along the genome was counted. Next, a smoothed profile of these events with a 401 bp moving window around each base pair and fitting a ZINBA-like mixture model was generated. Then, a signal threshold was set to determine whether a region was a peak signal or noise based on an odds ratio of 1/5. Finally, peaks within 500 bp of each other were merged to produce a position-sorted BED file.
Cell calling and peak-barcode matrix: For each barcode, the mapped high-quality fragments that passed all filters were recorded, and the number of fragments that overlapped any peak regions was used to separate the signal from noise. To capture the signal and noise, a mixture model of two negative binomial distributions was set, and barcodes that corresponded to real cells from the non-cell barcodes were separated by setting an odds ratio of 1000. Subsequently, a raw peak-barcode matrix consisting of the counts of fragment ends within each peak region for each barcode was produced. After filtering to contain only cell barcodes, the matrix was used in subsequent analyses, such as dimensionality reduction, clustering and visualization.
Genome_build: GRCh38
Supplementary_files_format_and_content: tsv files for barcodes; mtx files for matrix; bed files for peaks
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| Submission date |
Sep 20, 2020 |
| Last update date |
May 28, 2021 |
| Contact name |
Haiyan YU |
| E-mail(s) |
yuhaiyan@whu.edu.cn
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| Organization name |
Shenzhen People's Hospital
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| Street address |
No. 1017, North of Dongmen Road
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| City |
Shenzhen |
| ZIP/Postal code |
518020 |
| Country |
China |
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| Platform ID |
GPL23227 |
| Series (1) |
| GSE158263 |
Gene-regulatory network analysis of systemic lupus erythermatosus with a single-cell chromatin accessible assay |
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| Relations |
| BioSample |
SAMN16227049 |
| SRA |
SRX9158974 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM4795982_NC_PBMC_barcodes.tsv.gz |
32.6 Kb |
(ftp)(http) |
TSV |
| GSM4795982_NC_PBMC_matrix.mtx.gz |
30.2 Mb |
(ftp)(http) |
MTX |
| GSM4795982_NC_PBMC_peaks.bed.gz |
377.8 Kb |
(ftp)(http) |
BED |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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