Epigenetic profiling of hematopoietic stem cells and leukemia stem cells
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 15 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
- Mus musculus (mouse)
- Samples
- 15 samples: 15 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.
Read the full summary ↓
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 GSE29130_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 PRJNA140445 and SRA study SRP006724. 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 15 sample titles: 15 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.
- GSM721210 H3K79me2_MLL-AF9_huAML_ChIPSeq
- GSM721211 H3K79me2_normal_karyotype_huAML_ChIPSeq
- GSM721212 MLL-AF9_ChIPSeq
- GSM721213 H3K4me3_mHSC_ChIPSeq
- GSM721214 H3K4me3_mGMP_ChIPSeq
- GSM721215 H3K4me3_mLSC_ChIPSeq
- GSM721216 H3K27me3_mHSC_ChIPSeq
- GSM721217 H3K27me3_mGMP_ChIPSeq
- GSM721218 H3K27me3_mLSC_ChIPSeq
- GSM721219 H3K36me3_mHSC_ChIPSeq
- GSM721220 H3K36me3_mGMP_ChIPSeq
- GSM721221 H3K36me3_mLSC_ChIPSeq
- GSM721222 H3K79me2_mHSC_ChIPSeq
- GSM721223 H3K79me2_mGMP_ChIPSeq
- GSM721224 H3K79me2_mLSC_ChIPSeq
- GSE100041 Reduced representation bisulfite-sequencing of human leukemia cells and mouse hematopoietic progenitors 34 samples shares hematopoietic, leukemia
- GSE97442 Genetic and pharmacological restoration of TET2 function blocks stem cell self-renewal and progression of leukemia 80 samples shares leukemia, stem
- GSE277684 Premature senescence impairs hematopoietic stem cell function during sickle cell disease in mice and humans 52 samples shares hematopoietic, stem
- GSE241173 CD4+ T cell-derived IL21 regulates stem cell fate in acute myeloid leukemia by activation of p38-MAPK signaling 21 samples shares leukemia, stem
- GSE261742 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens 69 samples shares epigenetic
- GSE291268 Cardiac Radiotherapy-Induced Epigenetic Memory Underlies Electrophysiologic and Metabolic Reprogramming [ATAC-seq] 50 samples shares epigenetic
- GSE303627 MYST acetyltransferases are a targetable therapeutic vulnerability in SETBP1-mutant leukemia [CUT&Run] 46 samples shares leukemia
- GSE294955 ZFTA–RELA ependymomas make itaconate to epigenetically drive fusion expression [ChIP-Seq] 18 samples shares 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.