DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [CellCulture_WGBS]
DNA methylation · human · 12 samples
- What it is
- DNA methylationChemical marks on DNA that help switch genes on or off.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 12 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
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE319448_RAW.tar (it can run to tens of gigabytes).
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 beta-value tables or raw IDAT files among the supplementary files.
Also filed as BioProject PRJNA1423303 and SRA study SRP676898. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 3 samples read as cases, 3 as controls.
How we read this: Read from 12 sample titles: 12 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.
- GSM9518141 IDH2-mutant isogenic TF-1 DAC Rep 1, WGBS
- GSM9518142 IDH2-mutant isogenic TF-1 DAC Rep 2, WGBS
- GSM9518143 IDH2-mutant isogenic TF-1 DAC Rep 3, WGBS
- GSM9518144 IDH2-mutant isogenic TF-1 DMSO Rep 1, WGBS
- GSM9518145 IDH2-mutant isogenic TF-1 DMSO Rep 2, WGBS
- GSM9518146 IDH2-mutant isogenic TF-1 DMSO Rep 3, WGBS
- GSM9518147 TF-1 DAC Rep 1, WGBS
- GSM9518148 TF-1 DAC Rep 2, WGBS
- GSM9518149 TF-1 DAC Rep 3, WGBS
- GSM9518150 TF-1 DMSO Rep 1, WGBS
- GSM9518151 TF-1 DMSO Rep 2, WGBS
- GSM9518152 TF-1 DMSO Rep 3, WGBS
- GSE319444 DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [PrimaryAML_WGBS] 20 samples shares wgbs, aml, genetically-defined, stochasticity, methylation, variability, identifies
- GSE319461 DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML 82 samples shares aml, genetically-defined, stochasticity, methylation, variability, identifies
- GSE281087 DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [scRNAseq] 26 samples shares aml, genetically-defined, stochasticity, methylation, variability, identifies
- GSE319447 DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [PrimaryAML_scATACseq] 24 samples shares aml, genetically-defined, stochasticity, methylation, variability, identifies
- GSE256353 Upregulated cholesterol biosynthesis facilitates the survival of methylation-retaining AML cells following decitabine treatment [single_colony_TEM-Seq] 1728 samples shares aml, methylation
- GSE282258 Imaging-based drug screening combined with moleuclar profiling identifies signatures and drivers of therapy resistance in pediatric AML [ATAC-seq] 44 samples shares aml, identifies
- GSE282423 Imaging-based drug screening combined with moleuclar profiling identifies signatures and drivers of therapy resistance in pediatric AML [RNA-seq] 28 samples shares aml, identifies
- GSE232130 Leucegene: AML sequencing (GRCh38 reference) 691 samples shares aml
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.