Competition shapes the landscape of X-linked genetic diversity
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 4 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
- 4 samples: 4 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
- Competition shapes the landscape of X-chromosome-linked genetic diversityNature genetics · 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 GSE261622_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 PRJNA1088124 and SRA study SRP455422. 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 4 sample titles: 4 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.
- GSM7713478 Stag2-R370Q Atrx-Luc/bGal (FITC positive)
- GSM7713479 Stag2-WT (FITC negative)
- GSM8147518 STAG1/2 WT HAP1 ChIP
- GSM8147519 STAG1/2 MT HAP1 ChIP
- GSE317069 Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease 47 samples shares genetic
- GSE207516 Transcriptonal and epigenetic profiling of neuroblastoma cells based on CD49b expression 26 samples shares genetic
- GSE34260 Candida albicans induces monocyte training via epigenetic programming through a dectin 1-dependent pathway 15 samples shares genetic
- GSE308002 HTGTS-TCR-seq for profiling of mouse and human T-cell receptor α and β gene rearrangements and diversity 109 samples shares diversity
- GSE264571 Latent Epigenetic Programs in Müller Glia Contribute to Stress, Injury, and Disease Response in the Retina 87 samples shares genetic
- GSE97442 Genetic and pharmacological restoration of TET2 function blocks stem cell self-renewal and progression of leukemia 80 samples shares genetic
- GSE261742 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens 69 samples shares genetic
- GSE236831 Rapid CRISPR/Cas12a-based dual-crRNA library screening in high fidelity reveals novel genetic interactions during hepatocarcinogenesis 62 samples shares genetic
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.