← BioTransfer GEO Dataset Finder
GEO series

An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq

GSE303901 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 97 samples Submitted 2025/08/15 Platform GPL34281Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 97 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
97 samples: 97 samples, each with a distinct title — no replicated groupsGroups 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
An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seqbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
We developed Direct-Capture Targeted Perturb-seq (DC-TAP-seq), a cost-effective and sensitive approach that integrates U6-driven guide RNA capture with TAP-seq, enabling high-throughput screening of thousands of E–G connections at lower read depth. We applied this method to perform unbiased enhancer screens in two human cell types, K562 and WTC11. Our dataset revealed novel classes of non-canonical cis-regulatory elements (CREs) that were under-sampled in previous CRISPRi screens
Published in
An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq
Ray J, Jagoda E, Sheth MU et al. · bioRxiv : the preprint server for biology 2025 · PMID 41000760 · doi:10.1101/2025.09.16.676677
This dataset
Open GSE303901 in finder → Find more human 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 GSE303901_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1298184 and SRA study SRP604267. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41000760) ↗
Study design
97 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 19 samples read as cases, 36 as controls.

How we read this: Read from 97 sample titles: 97 distinct titles with little repetition. 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

+ 57 more — browse all 97 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.