DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [PrimaryAML_scATACseq]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 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
- 24 samples: 24 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 GSE319447_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 peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1423296 and SRA study SRP676889. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 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.
- GSM9518117 AML JH4198, scATAC-seq
- GSM9518118 AML JH4316, scMultiome ATAC
- GSM9518119 AML JH4639, scMultiome ATAC
- GSM9518120 AML JH5034, scMultiome ATAC
- GSM9518121 AML JH5205, scMultiome ATAC
- GSM9518122 AML JH5236, scATAC-seq
- GSM9518123 AML JH6048, scMultiome ATAC
- GSM9518124 AML SU048, scATAC-seq
- GSM9518125 AML SU050, scATAC-seq
- GSM9518126 AML SU070, scATAC-seq
- GSM9518127 AML SU075, scMultiome ATAC
- GSM9518128 AML SU204, scATAC-seq
- GSM9518129 AML SU209, scATAC-seq
- GSM9518130 AML SU214 Replicate 1, scATAC-seq
- GSM9518131 AML SU214 Replicate 2, scMultiome ATAC
- GSM9518132 AML SU227, scMultiome ATAC
- GSM9518133 AML SU270, scATAC-seq
- GSM9518134 AML SU344, scATAC-seq
- GSM9518135 AML SU494, scMultiome ATAC
- GSM9518136 AML SU504, scMultiome ATAC
- GSM9518137 AML SU758, scMultiome ATAC
- GSM9518138 CD34-1, scATAC-seq
- GSM9518139 CD34+ JH4308, scMultiome ATAC
- GSM9518140 GMP-1, scATAC-seq
- 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, convergent, epigenetic
- 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 aml, genetically-defined, stochasticity, methylation, variability, identifies, convergent, epigenetic
- GSE319448 DNA methylation stochasticity is linked to transcriptional variability and identifies convergent epigenetic disruption across genetically-defined subtypes of AML [CellCulture_WGBS] 12 samples shares aml, genetically-defined, stochasticity, methylation, variability, identifies, convergent, epigenetic
- GSE304097 DNA methylation profiling identifies long-range epigenetic silencing of clustered protocadherins as a key determinant of meningioma progression 293 samples shares methylation, identifies, epigenetic
- 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
- GSE256353 Upregulated cholesterol biosynthesis facilitates the survival of methylation-retaining AML cells following decitabine treatment [single_colony_TEM-Seq] 1728 samples shares aml, methylation
- 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
- GSE279619 SETD2 loss-of-function uniquely sensitizes cells to epigenetic targeting of NSD1-directed H3K36 methylation. 124 samples shares methylation, epigenetic
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.