← BioTransfer GEO Dataset Finder
GEO series

Improved spike-in normalization clarifies the relationship between active histone modifications and transcription

GSE286875 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 244 samples Submitted 2025/10/29 Platform GPL30173Platform GPL21697Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 244 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
244 samples: 214 distinct titles, 30 of them repeatedGroups 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)
Spike-in normalization enables quantitative analysis of ChIP-sequencing (ChIP-seq) signal. Here we introduce a novel robust dual-spike-in normalization approach for ChIP-seq (ChIP-wrangler) and revisit recent claims that active histone marks are dependent on transcription. Concerned that previous studies improperly used spike-in normalization to arrive at their conclusions, we used ChIP-wrangler to show that acute depletion of RNA polymerase II has only a modest impact on the levels of H3K4me3 and H3K27ac.
Read the full summary ↓
In line with other studies, our results provide proof that the maintenance of histone acetylation is not merely a consequence of ongoing transcription. Our innovative ChIP-seq normalization approach provides increased rigor and “guardrails” for successful spike-in normalization, and as applied here refines the understanding of the intricate crosstalk between RNA polymerase II activity and histone marks associated with transcription
This dataset
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.

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 GSE286875_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1217867 and SRA study SRP560966. Searching any of these in the dataset finder brings you back here.

Study design
214 distinct titles, 30 of them repeated
HeLa-S3, Triptolide treated, 0hr, biological … ×2 HeLa-S3, Triptolide treated, 0hr, biological … ×2 HeLa-S3, Triptolide treated, 1hr, biological … ×2 HeLa-S3, Triptolide treated, 1hr, biological … ×2 HeLa-S3, Triptolide treated, 4hr, biological … ×2 HeLa-S3, Triptolide treated, 4hr, biological … ×2 HCT116, DMSO treated, 0hr, biological replica… ×2 HCT116, auxin 1hr, biological replicate 1, H3… ×2 +22 more

Supports a case/control comparison: 30 samples read as cases, 58 as controls.

How we read this: Read from 244 sample titles: 214 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

+ 204 more — browse all 244 samples with per-sample file links →

Datasets on a similar topic

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.