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Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens

GSE261742 Mus musculus (mouse) Single-cell RNA-seq 69 samples Submitted 2025/09/12 Platform GPL28457Platform GPL30172Platform GPL30173
At a glance

Single-cell RNA-seq · mouse · 69 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
69 samples: 34 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 GSE261742 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 GSE261742_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 PRJNA1088519 and SRA study SRP495517. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
34 conditions, mostly in duplicate
Activated-Kat5_ATAC4 ×2 Activated-Kat5_ATAC7 ×2 Activated-Kat8_ATAC3 ×2 Activated-Mock_ATAC7 ×2 Activated-NtC5_ATAC3 ×2 Activated-NtC5_ATAC4 ×2 Activated-NtC5_ATAC5 ×2 Activated-NtC5_ATAC ×2 +27 more

Supports a between-group comparison across 68 samples.

How we read this: 34 replicated groups read from 69 sample titles; they account for 68 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

+ 29 more — browse all 69 samples with per-sample file links →

Datasets on a similar topic

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

Share this dataset

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