Time course single-cell RNA-seq and single-cell ATAC-seq data from mESCs treated with retinoic acid
Single-cell RNA-seq · mouse · 16 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
- 16 samples: 6 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.
- Paper
- Modeling combinatorial regulation from single-cell multi-omics provides regulatory units underpinning cell type landscape using cRegulonGenome biology · 2025
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE227320_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA944641 and SRA study SRP427268. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 14 samples.
How we read this: 6 replicated groups read from 16 sample titles; they account for 14 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.
- GSM7096413 scATACseq for Day 0, replicate 1 scATACseq for Day 0,
- GSM7096414 scATACseq for Day 0, replicate 2 scATACseq for Day 0,
- GSM7096415 scATACseq for Day 2, replicate 1
- GSM7096416 scATACseq for Day 4, replicate 1 scATACseq for Day 4,
- GSM7096417 scATACseq for Day 4, replicate 2 scATACseq for Day 4,
- GSM7096418 scATACseq for Day 10, replicate 1 scATACseq for Day 10,
- GSM7096419 scATACseq for Day 10, replicate 2 scATACseq for Day 10,
- GSM7096420 scATACseq for Day 10, replicate 3 scATACseq for Day 10,
- GSM7096421 scRNAseq for Day 0, replicate 1 scRNAseq for Day 0,
- GSM7096422 scRNAseq for Day 0, replicate 2 scRNAseq for Day 0,
- GSM7096423 scRNAseq for Day 2, replicate 1
- GSM7096424 scRNAseq for Day 4, replicate 1 scRNAseq for Day 4,
- GSM7096425 scRNAseq for Day 4, replicate 2 scRNAseq for Day 4,
- GSM7096426 scRNAseq for Day 10, replicate 1 scRNAseq for Day 10,
- GSM7096427 scRNAseq for Day 10, replicate 2 scRNAseq for Day 10,
- GSM7096428 scRNAseq for Day 10, replicate 3 scRNAseq for Day 10,
- GSE264278 TIme-cource single-cell RNA-seq analysis of bleomycin and LPS-induced lung injury and fibrosis 18 samples shares single-cell, rna-seq, time
- GSE312302 NMuMG PBRM1 RNA-seq, ATAC-seq, and ChIP-seq 171 samples shares atac-seq, rna-seq
- GSE292377 Step-wise signal integration governs adaptive programming of lymphocytes [bulkRNA-seq and ATAC-seq] 41 samples shares atac-seq, rna-seq
- GSE327645 BACH1 acts as a pioneer repressor to enable macrophage plasticity and adaptation across tissues and inflammatory contexts [RNA-seq/ATAC-seq] 28 samples shares atac-seq, rna-seq
- GSE300288 Single-cell and spatial transcriptomics analysis of tobacco-associated lung adenocarcinoma development, and in response to targeting inflammation alone or in combination with immune checkpoint blockade in precancerous phase [scRNA-seq] 31 samples shares single-cell, rna-seq
- GSE274125 Timestamp tracing delineates thymic regulatory T cell ontogeny in native conditions [scRNA-seq] 20 samples shares rna-seq, time
- GSE262879 Single-cell RNA-sequencing of murine pancreatic tumors derived from the orthotopic transplantation of Smad4 wild-type (WT) or Smad4 knockout (KO) pancreatic ductal adenocarcinoma (PDAC) KPC organoids in nu/nu mice. 18 samples shares single-cell, rna-seq
- GSE227108 Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells (scRNA-seq) 18 samples shares single-cell, rna-seq
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.