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Systematic Benchmarking of CUT&Tag Improves the Reliability and Reproducibility of Chromatin Analysis [Cell number]

GSE310695 Rattus norvegicus (rat) ChIP-seq / ATAC-seq (genome binding and open chromatin) 70 samples Submitted 2026/07/16 Platform GPL34316Platform GPL34290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · rat · 70 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
Rattus norvegicus (rat)
Samples
70 samples: 24 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Cleavage under target and tagementation (CUT&Tag) is a widely used assay for analyzing epigenomic localization of proteins and histone PTMs. This study is focused on increasing the reproducibility of CUT&Tag through standardization of both wet bench and downstream data analysis. We find that 10K cells is the minimum input requirement for robust genome-wide profiling of H3K7me3 in mESCs and rat C6 cells. For CTCF 50K cells are needed. EGS crosslinking and de-duplication strategies were also explored.
This dataset
Open GSE310695 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 GSE310695_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 PRJNA1366954 and SRA study SRP647234. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
24 conditions, mostly in triplicate
mESC H3K27me3 - 10K cells ×3 mESC H3K27me3 - 50K cells ×3 mESC H3K27me3 - 100K cells ×3 mESC CTCF - 1K cells ×3 mESC CTCF - 10K cells ×3 mESC CTCF - 50K cells ×3 mESC CTCF - 100K cells ×3 mESC IgG - 1K cells ×3 +16 more

Supports a between-group comparison across 70 samples.

How we read this: 24 replicated groups read from 70 sample titles; they account for 70 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

+ 30 more — browse all 70 samples with per-sample file links →

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Search all ChIP / ATAC / CUT&Tag 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.