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DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [PrimaryAML_WGBS]

GSE319444 Homo sapiens (human) DNA methylation 20 samples Submitted 2026/03/09 Platform GPL20301Platform GPL24676
At a glance

DNA methylation · human · 20 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
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
DNA Methylation Stochasticity Is Linked to Transcriptional Variability and Convergent Epigenetic Disruption across Genetic Subtypes of Acute Myeloid LeukemiaCancer research · 2026
Summary (written by the submitters)
Epigenetic regulators are frequently mutated in acute myeloid leukemia (AML). We investigated DNA methylation stochasticity in genetic subtypes of AML using WGBS data and publicly-available ERRBS data, and identified transcriptional dysregulation and altered chromatin accessibility related to methylation entropy using single-cell RNA-seq and single-cell ATAC-seq data.
Published in
DNA Methylation Stochasticity Is Linked to Transcriptional Variability and Convergent Epigenetic Disruption across Genetic Subtypes of Acute Myeloid Leukemia
Hilgart E, Zhou W, Martinez-Montes E et al. · Cancer research 2026 · PMID 41838954 · doi:10.1158/0008-5472.CAN-25-5822
This dataset
Open GSE319444 in finder → Find more human methylation 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 GSE319444_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 beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA1423294 and SRA study SRP676897. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41838954) ↗
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.