Mapping the male mouse chromatin accessibility landscape by UUATAC-seq
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 33 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
- 33 samples: 33 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
- Modeling the vertebrate regulatory sequence landscape by UUATAC-seq and deep learningCell · 2025
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 GSE264229_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 PRJNA1097004 and SRA study SRP500109. 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 33 sample titles: 33 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.
- GSM8214738 UUATAC-seq datasets of MouseMale_BoneMarrow
- GSM8214739 UUATAC-seq datasets of MouseMale_BrainStem
- GSM8214740 UUATAC-seq datasets of MouseMale_Cerebellum
- GSM8214741 UUATAC-seq datasets of MouseMale_Hypothalamus
- GSM8214742 UUATAC-seq datasets of MouseMale_LargeIntestine
- GSM8214743 UUATAC-seq datasets of MouseMale_LymphNode
- GSM8214744 UUATAC-seq datasets of MouseMale_Pituitary
- GSM8214745 UUATAC-seq datasets of MouseMale_SmallIntestine
- GSM8214746 UUATAC-seq datasets of MouseMale_SpinalCord
- GSM8214747 UUATAC-seq datasets of MouseMale_Stomach
- GSM8214748 UUATAC-seq datasets of MouseMale_Telencephalon
- GSM8214750 UUATAC-seq datasets of MouseMale_Bladder_A
- GSM8214751 UUATAC-seq datasets of MouseMale_Bladder_B
- GSM8214752 UUATAC-seq datasets of MouseMale_Heart_A
- GSM8214753 UUATAC-seq datasets of MouseMale_Heart_B
- GSM8214754 UUATAC-seq datasets of MouseMale_Kidney_A
- GSM8214755 UUATAC-seq datasets of MouseMale_Kidney_B
- GSM8214756 UUATAC-seq datasets of MouseMale_Liver_A
- GSM8214757 UUATAC-seq datasets of MouseMale_Liver_B
- GSM8214758 UUATAC-seq datasets of MouseMale_Lung_A
- GSM8214759 UUATAC-seq datasets of MouseMale_Lung_B
- GSM8214760 UUATAC-seq datasets of MouseMale_Muscle_A
- GSM8214761 UUATAC-seq datasets of MouseMale_Muscle_B
- GSM8214762 UUATAC-seq datasets of MouseMale_Pancreas_A
- GSM8214763 UUATAC-seq datasets of MouseMale_Pancreas_B
- GSM8214764 UUATAC-seq datasets of MouseMale_Prostate_A
- GSM8214765 UUATAC-seq datasets of MouseMale_Prostate_B
- GSM8214766 UUATAC-seq datasets of MouseMale_Spleen_A
- GSM8214767 UUATAC-seq datasets of MouseMale_Spleen_B
- GSM8214768 UUATAC-seq datasets of MouseMale_Testis_A
- GSM8214769 UUATAC-seq datasets of MouseMale_Testis_B
- GSM8214770 UUATAC-seq datasets of MouseMale_Thymus_A
- GSM8214771 UUATAC-seq datasets of MouseMale_Thymus_B
- GSE249077 Mapping the female mouse chromatin accessibility landscape by UUATAC-seq 23 samples shares accessibility, uuatac-seq, chromatin, mapping, male
- GSE216371 A single-cell atlas of chromatin accessibility in mouse organogenesis 68 samples shares accessibility, chromatin
- GSE310322 Mapping self-associating chromatin hubs identifies Id proteins as key determinants of exhausted T cell fate 37 samples shares chromatin, mapping
- GSE246986 Ki67-mediated chromatin accessibility impedes B-cell antigen-receptor gene rearrangement 24 samples shares accessibility, chromatin
- GSE342565 Chromatin accessibility profiling of high endothelial cells (HECs) from mouse peripheral lymph node and Peyer's patch by ATAC-seq 2 samples shares accessibility, chromatin
- GSE274040 Transcriptional and chromatin accessibility landscapes of hematopoiesis in a mouse model of breast cancer 16 samples shares accessibility, chromatin
- GSE309545 Inflammatory signaling differentially changes chromatin accessibility and gene expression of the PD-associated kinase LRRK2 between human and mice [multiome mouse] 64 samples shares accessibility, chromatin
- GSE283483 Novel environment exposure drives temporally defined and region-specific chromatin accessibility and gene expression programs in the hippocampus 160 samples shares accessibility, chromatin
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.