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Unlocking single cell chromatin accessibility in formalin-fixed paraffin-embedded tissues by scFFPE-ATAC [mouse]

GSE306401 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/10/14 Platform GPL34328
At a glance

Single-cell RNA-seq · mouse · 2 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
2 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.
Paper
scFFPE-ATAC enables high-throughput single cell chromatin accessibility profiling in formalin-fixed paraffin-embedded samplesNature communications · 2025
Summary (written by the submitters)
Formalin-fixed paraffin-embedded (FFPE) samples are the gold standard for clinical tissue preservation. However, single-cell chromatin accessibility profiling technology, a powerful tool to understand epigenetic regulation in human disease, is not available for FFPE samples due to extensive DNA damage.
Read the full summary ↓
To solve this technical challenge, we introduce scFFPE-ATAC by integrating uniquely designed DNA oligos on Tn5 transposase, split-and-pool ligation DNA barcoding, T7 promoter-mediated DNA damage rescue, and in vitro transcription—the first high-throughput single-cell chromatin accessibility assay for FFPE samples. scFFPE-ATAC enables the simultaneous profiling of up to 64 FFPE samples or spatial regions, with 884,736 cell barcodes in a single run. We successfully applied scFFPE-ATAC to clinical FFPE human lymph nodes stored for 8–15 years and identified distinct epigenetic regulators between tumor centers and invasive edge epithelial cells in human lung cancer. Additionally, we analyzed paired primary and relapsed follicular lymphoma (FL), as well as FL transformed into diffuse large B-cell lymphoma, from clinical samples archived for 2–7 years, revealing key epigenetic drivers of tumor progression. Overall, scFFPE-ATAC enables high-throughput, high-sensitivity chromatin accessibility profiling in long-term archived clinical specimens, paving the way for retrospective epigenetic studies and spatial epigenetic analysis. This technology provides a powerful tool for understanding tumor relapse and metastasis, with broad applications in basic research and personalized medicine.
Published in
scFFPE-ATAC enables high-throughput single cell chromatin accessibility profiling in formalin-fixed paraffin-embedded samples
Yadav RP, Xing P, Zhao M et al. · Nature communications 2025 · PMID 41238550 · doi:10.1038/s41467-025-66170-4
This dataset
Open GSE306401 in finder → Find more mouse 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 GSE306401_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 PRJNA1310572 and SRA study SRP612317. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41238550) ↗
Samples in this study

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Datasets on a similar topic

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