Spatial-Mux-seq: Multiplexed spatial mapping of chromatin features, transcriptome, and proteins at tissue scale
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 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
- 12 samples: 12 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
- Multiplexed spatial mapping of chromatin features, transcriptome, and proteins in tissuesbioRxiv : the preprint server for biology · 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 GSE263333_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 PRJNA1096722 and SRA study SRP500005. 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 12 sample titles: 12 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.
- GSM8189704 ME13_50um_1_H3K27me3_H3K27ac
- GSM8189705 ME13_50um_2_H3K27me3_H3K27ac
- GSM8189706 ME13_50um_3_ATAC_H3K4me3_H3K27me3
- GSM8189707 ME13_50um_3_RNA
- GSM8189708 ME13_20um_H3K4me3_H3K27me3
- GSM8189709 ME13_20um_RNA
- GSM8189710 ME13_20um_protein
- GSM8189711 P21_brain_20um_H3K27ac_H3K27me3
- GSM8189712 P21_brain_20um_RNA
- GSM8494157 5M_20um_ATAC_H3K27ac_H3K27me3
- GSM8494158 5M_20um_RNA
- GSM8494159 5M_20um_protein
- GSE310322 Mapping self-associating chromatin hubs identifies Id proteins as key determinants of exhausted T cell fate 37 samples shares chromatin, proteins, mapping
- GSE264229 Mapping the male mouse chromatin accessibility landscape by UUATAC-seq 33 samples shares chromatin, mapping
- GSE249077 Mapping the female mouse chromatin accessibility landscape by UUATAC-seq 23 samples shares chromatin, mapping
- GSE283662 Multiscale integration of tissue and chromatin context converts cell heterogeneity into stable intestinal patterning 22 samples shares chromatin, scale
- GSE305054 Mapping early PRC2 nucleation sites upon Suz12 reintroduction reveals features of de novo Polycomb recruitment 18 samples shares features, mapping
- GSE307620 Spatial chromatin architecture and accessibility co-profiling of mammalian tissues 2 samples shares chromatin, spatial
- GSE72539 CTCF binding polarity determines chromatin looping [4C] 504 samples shares chromatin
- GSE166225 Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback between de novo DNA methylation and chromatin condensates [RNA-seq] 288 samples shares 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.