GEO series

CUT&Tag recovers up to half of ENCODE ChIP-seq histone acetylation peaks

GSE286492 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 38 samples Submitted 2025/01/14 Platform GPL20301

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 38 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: 38 samples: 38 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: CUT&Tag recovers up to half of ENCODE ChIP-seq histone acetylation peaksNature communications · 2025

Summary (written by the submitters)

We comprehensively benchmarked CUT&Tag for H3K27ac and H3K27me3 against published ChIP-seq profiles from ENCODE in K562 cells. Combining multiple new and published CUT&Tag datasets, there was an average recall of 54% known ENCODE peaks for both histone modifications. To optimize data analysis steps, we tested peak callers MACS2 and SEACR and identified optimal peak calling parameters.

Read the full summary ↓

Considering both precision and recall of known ENCODE peaks, the peak callers were comparable in their performance, although peaks produced by MACS2 match ENCODE peak width distributions more closely. We found that reducing PCR cycles during library preparation lowered duplication rates at the expense of ENCODE peak recovery. Despite the moderate ENCODE peak recovery, peaks identified by CUT&Tag represent the strongest ENCODE peaks and show the same functional and biological enrichments as ChIP-seq peaks identified by ENCODE. Our workflow systematically evaluates the merits of methodological adjustments, providing a benchmarking framework for the experimental design and analysis of CUT&Tag studies, and will facilitate future efforts to apply CUT&Tag in human tissues and single cells.

Published in

CUT&Tag recovers up to half of ENCODE ChIP-seq histone acetylation peaks

Abbasova L, Urbanaviciute P, Hu D et al. · Nature communications 2025 · PMID 40148272 · doi:10.1038/s41467-025-58137-2

This dataset

Open GSE286492 in finder → Find more human 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 GSE286492_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 PRJNA1209791 and SRA study SRP556860. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40148272) ↗

Study design

38 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 38 sample titles: 38 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

GSM8728355 Abcam-ab177178, 1/100, 15 PCR, SDS, replicate 1 [H3K27ac]
GSM8728356 Abcam-ab177178, 1/100, 15 PCR, SDS, replicate 2 [H3K27ac]
GSM8728357 Abcam-ab4729, 1/100, 15 PCR, SDS, replicate 1 [H3K27ac]
GSM8728358 Abcam-ab4729, 1/100, 15 PCR, SDS, replicate 2 [H3K27ac]
GSM8728359 Diagenode C15410196, 1/50, 15 PCR, SDS, replicate 1 [H3K27ac]
GSM8728360 Diagenode C15410196, 1/50, 15 PCR, SDS, replicate 2 [H3K27ac]
GSM8728361 CST 9733, 1/100, 15 PCR, SDS, replicate 1 [H3K27me3]
GSM8728362 CST 9733, 1/100, 15 PCR, SDS, replicate 2 [H3K27me3]
GSM8728363 Abcam-ab177178, 1/100, 15 PCR, SDS [H3K27ac]
GSM8728364 Abcam-ab4729, 1/100, 15 PCR, SDS [H3K27ac]
GSM8728365 Active Motif 39133, 1/100, 15 PCR, SDS [H3K27ac]
GSM8728366 CST9733, 1/100, 15 PCR, SDS [H3K27me3]
GSM8728367 Diagenode C15410196, 1/100, 15 PCR, SDS [H3K27ac]
GSM8728368 Diagenode C15410196, 1/50, 15 PCR, SDS [H3K27ac]
GSM8728369 Abcam-ab177178, 1/100, 15 PCR, SDS +TSA [H3K27ac]
GSM8728370 Abcam-ab4729, 1/100, 15 PCR, SDS +TSA [H3K27ac]
GSM8728371 Diagenode C15410196, 1/100, 15 PCR, SDS +TSA [H3K27ac]
GSM8728372 Diagenode C15410196, 1/50, 15 PCR, SDS +TSA [H3K27ac]
GSM8728373 Abcam-ab177178, 1/100, 11 PCR, SDS [H3K27ac]
GSM8728374 Abcam-ab4729, 1/100, 11 PCR, SDS [H3K27ac]
GSM8728375 Active Motif 39133, 1/100, 11 PCR, SDS [H3K27ac]
GSM8728376 CST9733, 1/100, 11 PCR, SDS [H3K27me3]
GSM8728377 Diagenode C15410196, 1/50, 11 PCR, SDS [H3K27ac]
GSM8728378 Abcam-ab177178, 1/100, 11 PCR, column [H3K27ac]
GSM8728379 Abcam-ab4729, 1/100, 11 PCR, column [H3K27ac]
GSM8728380 Active Motif 39133, 1/100, 11 PCR, column [H3K27ac]
GSM8728381 CST9733, 1/100, 11 PCR, column [H3K27me3]
GSM8728382 Diagenode C15410196, 1/50, 11 PCR, column [H3K27ac]
GSM8728383 Abcam-ab177178, 1/100, 13 PCR, SDS [H3K27ac]
GSM8728384 Abcam-ab4729, 1/100, 13 PCR, SDS [H3K27ac]
GSM8728385 Active Motif 39133, 1/100, 13 PCR, SDS [H3K27ac]
GSM8728386 CST9733, 1/100, 13 PCR, SDS [H3K27me3]
GSM8728387 Diagenode C15410196, 1/50, 13 PCR, SDS [H3K27ac]
GSM8728388 Abcam-ab177178, 1/100, 13 PCR, column [H3K27ac]
GSM8728389 Abcam-ab4729, 1/100, 13 PCR, column [H3K27ac]
GSM8728390 Active Motif 39133, 1/100, 13 PCR, column [H3K27ac]
GSM8728391 CST9733, 1/100, 13 PCR, column [H3K27me3]
GSM8728392 Diagenode C15410196, 1/50, 13 PCR, column [H3K27ac]

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