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RSK1 is an exploitable dependency in myeloid malignancies.

GSE228760 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 191 samples Submitted 2024/11/13 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 191 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
191 samples: 66 conditions, mostly in duplicateGroups 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
RSK1 is an exploitable dependency in myeloproliferative neoplasms and secondary acute myeloid leukemiaNature communications · 2025
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
RSK1 is an exploitable dependency in myeloproliferative neoplasms and secondary acute myeloid leukemia
Kong T, Laranjeira ABA, Letson CT et al. · Nature communications 2025 · PMID 39820365 · doi:10.1038/s41467-024-55643-7
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 GSE228760_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 PRJNA951429 and SRA study SRP430505. Searching any of these in the dataset finder brings you back here.

Study design
66 conditions, mostly in duplicate
THP-1 PMD H3K27ac ×3 THP-1 DMSO ×3 THP-1 PMD ×3 HEL DMSO ×2 HEL PMD ×2 MV4-11 DMSO ×2 MV4-11 PMD ×2 MV4-11 Quiz ×2 +114 more

Supports a between-group comparison across 135 samples.

How we read this: 66 replicated groups read from 191 sample titles; they account for 135 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

+ 151 more — browse all 191 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.