GEO series

Single-cell chromatin accessibility data using scATAC-seq

GSE65360 Homo sapiens (human) Single-cell RNA-seq 1632 samples Submitted 2015/06/17 Platform GPL19057Platform GPL15520Platform GPL16791Platform GPL18573

At a glance

Single-cell RNA-seq · human · 1632 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 1632 samples
Data you can get: A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.

Summary (written by the submitters)

Cell-to-cell variation is a universal feature of life that impacts a wide range of biological phenomena, from developmental plasticity to tumor heterogeneity. While recent advances have improved our ability to document cellular phenotypic variation the fundamental mechanisms that generate variability from identical DNA sequences remain elusive.

Read the full summary ↓

Here we reveal the landscape and principles of cellular DNA regulatory variation by developing a robust method for mapping the accessible genome of individual cells via assay of transposase accessible chromatin sequencing (ATAC-seq). Single-cell ATAC-seq (scATAC-seq) maps from hundreds of single-cells in aggregate closely resemble accessibility profiles from tens of millions of cells and provides insights into cell-to-cell variation. Accessibility variance is systematically associated with specific trans-factors and cis-elements, and we discover combinations of trans-factors associated with either induction or suppression of cell-to-cell variability. We further identify sets of trans-factors associated with cell-type specific accessibility variance across 6 cell types. Targeted perturbations of cell cycle or transcription factor signaling evoke stimulus-specific changes in this observed variability. The pattern of accessibility variation in cis across the genome recapitulates chromosome topological domains de novo, linking single-cell accessibility variation to three-dimensional genome organization. All together, single-cell analysis of DNA accessibility provides new insight into cellular variation of the “regulome.”

This dataset

Open GSE65360 in finder → Find more ChIP / ATAC / CUT&Tag datasets →

Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE65360_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA274006 and SRA study SRP052977. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26083756) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 1632 more — browse all 1632 samples with per-sample file links →

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GSE67446 Multiplex Single Cell Profiling of Chromatin Accessibility by Combinatorial Cellular Indexing [ATAC-seq] 6 samples shares accessibility, chromatin
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GSE132266 scChIC-seq reveals focusing of global chromatin domains during differentiation 80 samples shares chromatin
GSE283706 Af-CUT&Tag: A Sensitive and Antibody-Free Chromatin Profiling Method Using Genetically Encoded Tags and High-Affinity Binders Fused to Tn5 65 samples shares chromatin
GSE320163 Minimizing far-extending chromatin perturbation in genome editing preserves stem cell identity [ATAC-Seq] 377 samples shares chromatin

Search all ChIP / ATAC / CUT&Tag datasets in GEO →

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