C-terminal Mutations in RUNX1 Induce Differentiation Block and Alter Transcription through Changes in Enhancer-Promoter Interactions
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 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
- 16 samples: 6 conditions, mostly in duplicateGroups 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
- RUNX1 C-terminal mutations impair blood cell differentiation by perturbing specific enhancer-promoter networksBlood advances · 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 GSE236644_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 PRJNA991944 and SRA study SRP447796. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 14 samples.
How we read this: 6 replicated groups read from 16 sample titles; they account for 14 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.
- GSM7566851 WT_ChIP_Input
- GSM7566852 WT_ChIP_1 WT_ChIP
- GSM7566853 WT_ChIP_2 WT_ChIP
- GSM7566854 RUNX1R320_Input
- GSM7566855 RUNX1R320_1 RUNX1R320
- GSM7566856 RUNX1R320_2 RUNX1R320
- GSM7566870 WT_GRID_1 WT_GRID
- GSM7566871 WT_GRID_2 WT_GRID
- GSM7566872 RUNX1R320_GRID_1 RUNX1R320_GRID
- GSM7566873 RUNX1R320_GRID_2 RUNX1R320_GRID
- GSM7566874 WT_RNA_1 WT_RNA
- GSM7566875 WT_RNA_2 WT_RNA
- GSM7566876 WT_RNA_3 WT_RNA
- GSM7566877 RUNX1R320_RNA_1 RUNX1R320_RNA
- GSM7566878 RUNX1R320_RNA_2 RUNX1R320_RNA
- GSM7566879 RUNX1R320_RNA_3 RUNX1R320_RNA
- GSE275721 Lineage master regulator and cancer-selective partner transcription factors rewire 3D genome topology for tumor-specific gene control 72 samples shares transcription
- GSE314310 Cardiopedia-Ligand: a Ligand Stimulation Atlas for Cardiac Function and Transcriptional Response 468 samples shares transcription
- GSE303576 Rb-driven transcription limits its tumour suppressive effects in breast cancer 279 samples shares transcription
- GSE22098 Whole blood transcriptional profiles of patients with active tuberculosis (TB) and other inflammatory and infectious diseases 274 samples shares transcription
- GSE303478 Systematic investigation reveals extensive Epstein-Barr virus transcriptional regulation of the human genome 217 samples shares transcription
- GSE271676 Spatial Transcriptional Landscape of Human Heart Failure 178 samples shares transcription
- GSE274546 The Multi-Layered Transcriptional Architecture of Glioblastoma Ecosystems [10X] 121 samples shares transcription
- GSE299348 Single-cell epigenetic, transcriptional, protein, and TCR states of HIV-1-infected cells in gut 117 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.