← BioTransfer GEO Dataset Finder
GEO series

2cChIP-seq: an efficient and reliable method for epigenomic profiling of small cell numbers and single cells

GSE185619 Homo sapiens (human) Single-cell RNA-seq 231 samples Submitted 2024/10/27 Platform GPL21273Platform GPL20795Platform GPL19057
At a glance

Single-cell RNA-seq · human · 231 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
231 samples: 18 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
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.
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
This dataset
Open GSE185619 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 GSE185619_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 PRJNA770513 and SRA study SRP303286. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in duplicate
ESC_H3K4me3_exp1_cell ×96 ESC_H3K4me3_exp2_cell ×96 K562_H3K4me3_1K_cells_2cChIP-seq ×2 K562_H3K4me3_100_cells_2cChIP-seq ×2 K562_H3K4me3_50_cells_2cChIP-seq ×2 K562_H3K4me3_10_cells_2ChIP-seq ×2 K562_H3K27ac_1K_cells_2cChIP-seq ×2 K562_H3K27ac_100_cells_2cChIP-seq ×2 +17 more

Supports a between-group comparison across 224 samples.

How we read this: 18 replicated groups read from 231 sample titles; they account for 224 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 191 more — browse all 231 samples with per-sample file links →

Datasets on a similar topic

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

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.