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Effect of TWIST1 dosage changes on chromatin accessibility in hESC-derived cranial neural crest cells

GSE267008 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2024/06/26 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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
20 samples: 20 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
Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosagebioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
To assess the effects of quantitative TWIST1 dosage changes on chromatin accessibility in hESC-derived cranial neural crest cells, we performed genome editing of the H9 hESC lines to tag TWIST1 with FKBPV36 and V5, Upon differentiating edited hESC to cranial neural crest cells using an established protocol, addition of differing concentrations of the degrader molecule dTAGV-1 results in different TWIST1 concentrations, as measured by V5 intracellular staining and flow cytometry. We then profiled chromatin accessibility in each of these TWIST1 concentrations
Published in
Transfer learning reveals sequence determinants of the quantitative response to transcription factor dosage
Naqvi S, Kim S, Tabatabaee S et al. · bioRxiv : the preprint server for biology 2024 · PMID 38853998 · doi:10.1101/2024.05.28.596078
This dataset
Open GSE267008 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 GSE267008_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 PRJNA1109336 and SRA study SRP506499. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38853998) ↗
Study design
20 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 20 sample titles: 20 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
Datasets on a similar topic

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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.