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Adipose tissue retains an epigenetic memory of obesity after weight loss

GSE236580 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 135 samples Submitted 2024/11/14 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 135 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
135 samples: 109 distinct titles, 16 of them repeatedGroups 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
Adipose tissue retains an epigenetic memory of obesity after weight lossNature · 2024
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
Adipose tissue retains an epigenetic memory of obesity after weight loss
Hinte LC, Castellano-Castillo D, Ghosh A et al. · Nature 2024 · PMID 39558077 · doi:10.1038/s41586-024-08165-7
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE236580_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA991586 and SRA study SRP447450. Searching any of these in the dataset finder brings you back here.

Study design
109 distinct titles, 16 of them repeated
C_short_ATAC ×3 H_short_ATAC ×3 CC_short_ATAC ×3 HC_short_ATAC ×3 HH_long_ATAC ×3 HHC_long_ATAC ×3 TRAP_C_short ×3 TRAP_H_short ×3 +8 more

How we read this: Read from 135 sample titles: 109 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.

Samples in this study

+ 95 more — browse all 135 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.