Redistribution of PU.1 partner transcription factor RUNX1 binding secures cell survival during leukemogenesis
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 79 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
- 79 samples: 19 conditions, mostly in triplicateGroups 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
- Redistribution of PU.1 partner transcription factor RUNX1 binding secures cell survival during leukemogenesisThe EMBO journal · 2024
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 GSE251674_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 PRJNA1055042 and SRA study SRP478980. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 10 samples read as cases, 26 as controls.
How we read this: 19 replicated groups read from 79 sample titles; they account for 59 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.
- GSM7982942 URE GMP, ATAC-seq, rep1 URE GMP, ATAC-seq,
- GSM7982943 URE GMP, ATAC-seq, rep2 URE GMP, ATAC-seq,
- GSM7982944 URE GMP, ATAC-seq, rep3 URE GMP, ATAC-seq,
- GSM7982945 URE LSK, ATAC-seq, rep1 URE LSK, ATAC-seq,
- GSM7982946 URE LSK, ATAC-seq, rep2 URE LSK, ATAC-seq,
- GSM7982947 URE LSK, ATAC-seq, rep3 URE LSK, ATAC-seq,
- GSM7982948 WT GMP, ATAC-seq, rep1 WT GMP, ATAC-seq,
- GSM7982949 WT GMP, ATAC-seq, rep2 WT GMP, ATAC-seq,
- GSM7982950 WT GMP, ATAC-seq, rep3 WT GMP, ATAC-seq,
- GSM7982951 WT LSK, ATAC-seq, rep1 WT LSK, ATAC-seq,
- GSM7982952 WT LSK, ATAC-seq, rep2 WT LSK, ATAC-seq,
- GSM7982953 WT LSK, ATAC-seq, rep3 WT LSK, ATAC-seq,
- GSM7982955 B22, RNA-seq, rep1 B22, RNA-seq,
- GSM7982956 B22, RNA-seq, rep2 B22, RNA-seq,
- GSM7982957 B22, RNA-seq, rep3 B22, RNA-seq,
- GSM7982958 HoxURE, RNA-seq, rep1 HoxURE, RNA-seq,
- GSM7982959 HoxURE, RNA-seq, rep2 HoxURE, RNA-seq,
- GSM7982960 HoxURE, RNA-seq, rep3 HoxURE, RNA-seq,
- GSM7982961 HoxWT, RNA-seq, rep1 HoxWT, RNA-seq,
- GSM7982962 HoxWT, RNA-seq, rep2 HoxWT, RNA-seq,
- GSM7982963 HoxWT, RNA-seq, rep3 HoxWT, RNA-seq,
- GSM7983026 URE_GMP, RNA-seq, rep1 URE_GMP, RNA-seq,
- GSM7983027 URE_GMP, RNA-seq, rep2 URE_GMP, RNA-seq,
- GSM7983028 URE_GMP, RNA-seq, rep3 URE_GMP, RNA-seq,
- GSM7983029 URE_GMP, RNA-seq, rep4 URE_GMP, RNA-seq,
- GSM7983030 URE_LSK, RNA-seq, rep1 URE_LSK, RNA-seq,
- GSM7983031 URE_LSK, RNA-seq, rep2 URE_LSK, RNA-seq,
- GSM7983032 URE_LSK, RNA-seq, rep3 URE_LSK, RNA-seq,
- GSM7983033 URE_LSK, RNA-seq, rep4 URE_LSK, RNA-seq,
- GSM7983034 WT_GMP, RNA-seq, rep1 WT_GMP, RNA-seq,
- GSM7983035 WT_GMP, RNA-seq, rep2 WT_GMP, RNA-seq,
- GSM7983036 WT_GMP, RNA-seq, rep3 WT_GMP, RNA-seq,
- GSM7983037 WT_GMP, RNA-seq, rep4 WT_GMP, RNA-seq,
- GSM7983038 WT_LSK, RNA-seq, rep1 WT_LSK, RNA-seq,
- GSM7983039 WT_LSK, RNA-seq, rep2 WT_LSK, RNA-seq,
- GSM7983040 WT_LSK, RNA-seq, rep3 WT_LSK, RNA-seq,
- GSM7983041 WT_LSK, RNA-seq, rep4 WT_LSK, RNA-seq,
- GSM7983261 URE, scRNA-seq, rep1 URE, scRNA-seq,
- GSM7983262 URE, scRNA-seq, rep2 URE, scRNA-seq,
- GSM7983263 WT, scRNA-seq, rep1 WT, scRNA-seq,
+ 39 more — browse all 79 samples with per-sample file links →
- GSE253753 Functional Characterization of Cooperating MGA Mutations in RUNX1::RUNX1T1 Acute Myeloid Leukemia 126 samples shares runx1
- GSE248942 Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration (ATAC-Seq) 123 samples shares runx1
- GSE253750 Functional Characterization of Cooperating MGA Mutations in RUNX1::RUNX1T1 Acute Myeloid Leukemia [Cut&Run] 87 samples shares runx1
- GSE253748 Functional Characterization of Cooperating MGA Mutations in RUNX1::RUNX1T1 Acute Myeloid Leukemia [RNA-seq] 29 samples shares runx1
- GSE248944 Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration (CUT&RUN) 14 samples shares runx1
- GSE289420 Astrocyte-derived cholesterol drives synaptic gene expression in developing neurons and reciprocal astrocytic transcriptional programs 416 samples shares transcription
- GSE241347 Chromatin-associated LTR RNA m5C oxidation by TET2 regulates leukemogenesis 291 samples shares leukemogenesis
- GSE261351 Direct measurement of RNA Polymerase II hypertranscription in cancer FFPE samples 278 samples shares transcription
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.