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Integrative genomic approach identifies glial transcriptomic dysregulation in the cortex of individuals with Alcohol Use Disorder

GSE247416 Homo sapiens (human) Single-cell RNA-seq 73 samples Submitted 2025/04/17 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 73 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
73 samples
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
Integrative Genomics Approach Identifies Glial Transcriptomic Dysregulation and Risk in the Cortex of Individuals With Alcohol Use DisorderBiological psychiatry · 2026
Summary (written by the submitters)
Nuclei were isolated from human postmartum brain frozen dorsolateral prefrontal cortex samples of AUD and control individuals. Libraries were prepared with 10X Genomics platform and sequenced using NovaSeq 6000. Post-filtering and site integration resulted in 464, 716 nuclei for downstream analysis.
Published in
Integrative Genomics Approach Identifies Glial Transcriptomic Dysregulation and Risk in the Cortex of Individuals With Alcohol Use Disorder
Warden AS, Salem NA, Brenner E et al. · Biological psychiatry 2026 · PMID 40024496 · doi:10.1016/j.biopsych.2025.02.895
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 GSE247416_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1037516 and SRA study SRP471148. Searching any of these in the dataset finder brings you back here.

Study design
A cohort of 73 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run Sample_35 … Sample_58 and carry no group information.

Samples in this study

+ 33 more — browse all 73 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.