← BioTransfer GEO Dataset Finder
GEO series

Single-Cell Chromatin Accessibility Landscape of Developing Perinatal Mouse Skin: A Multi-Omics Approach to Lineage Specification [scATAC-seq and scRNA-seq]

GSE286328 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2026/03/12 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 10 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
10 samples: 5 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
A multi-omic single-cell landscape of perinatal mouse skin maps lineage specification and reveals shared dynamics in human fetal skinExperimental & molecular medicine · 2026
Summary (written by the submitters)
This study presents a time-series scATAC analysis of developing mouse skin. Motif and footprint analyses at the chromatin level, as well as integrated analysis with single-cell and spatial transcriptomic data, enable an in-depth identification of key transcription factors and driver genes involved in fibroblast differentiation and hair follicle formation.
Read the full summary ↓
This study demonstrates the utility of scATAC analysis combined with multi-omics approaches in providing a comprehensive understanding of skin development. It serves as a valuable reference for future research on skin development and regeneration, supported by an interactive online portal.
Published in
A multi-omic single-cell landscape of perinatal mouse skin maps lineage specification and reveals shared dynamics in human fetal skin
Lee H, Lee S, Jo SJ et al. · Experimental & molecular medicine 2026 · PMID 41998142 · doi:10.1038/s12276-026-01692-5
This dataset
Open GSE286328 in finder → Find more mouse RNA-seq 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 GSE286328_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 PRJNA1208925 and SRA study SRP556452. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41998142) ↗
Study design
5 conditions, mostly in duplicate
Mouse, skin, E18.5, scATAC, ×2 Mouse, skin, PD0, scATAC, ×2 Mouse, skin, PD2, scATAC, ×2 Mouse, skin, PD4, scATAC, ×2 Mouse, skin, E18.5, scRNA, ×2

Supports a between-group comparison across 10 samples.

How we read this: 5 replicated groups read from 10 sample titles; they account for 10 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
Datasets on a similar topic

Search all mouse RNA-seq 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.