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Convergent transcriptomic signatures across brain structures in eating disorders and obsessive compulsive disorder

GSE262138 Homo sapiens (human) RNA-seq (gene expression) 338 samples Submitted 2024/12/18 Platform GPL21290
At a glance

RNA-seq (gene expression) · human · 338 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
338 samples: 170 × control, vs 114 × ED, vs 54 × OCD,Groups 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
Convergent molecular signatures across eating disorders and obsessive-compulsive disorder in the human brainmedRxiv : the preprint server for health sciences · 2024
Summary (written by the submitters)
The objective of this study was to delineate the transcriptomic landscapes of the caudate and dorsolateral prefrontal cortex (DLFPC) in individuals with ED and OCD to identify common and distinct molecular pathways that may underlie these disorders.
Published in
Convergent molecular signatures across eating disorders and obsessive-compulsive disorder in the human brain
Breen MS, Tao R, Yang A et al. · medRxiv : the preprint server for health sciences 2024 · PMID 39649579 · doi:10.1101/2024.11.27.24318078
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 GSE262138_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1090459 and SRA study SRP496996. Searching any of these in the dataset finder brings you back here.

Study design
170 × control, vs 114 × ED, vs 54 × OCD,

Supports a between-group comparison across 338 samples.

How we read this: 3 replicated groups read from 338 sample titles; they account for 338 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.

Samples in this study

+ 298 more — browse all 338 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.