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Quantification of Systemic Inflammation by a Gene Score Uncovers Relevant Features on Acutely Decompensated Cirrhosis

GSE239775 Homo sapiens (human) RNA-seq (gene expression) 1177 samples Submitted 2026/02/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 1177 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
1177 samples: 1177 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
Gene score to quantify systemic inflammation in patients with acutely decompensated cirrhosisGut · 2025
Summary (written by the submitters)
Acutely decompensated cirrhosis (ADC) is related to systemic inflammation (SI) due to activation of the innate-immune system. Acute-on-Chronic Liver Failure (ACLF) is the extreme expression of this process. We developed a gene score to quantify SI in ADC.
Published in
Gene score to quantify systemic inflammation in patients with acutely decompensated cirrhosis
Trebicka J, Aguilar F, Queiroz Farias A et al. · Gut 2025 · PMID 40011033 · doi:10.1136/gutjnl-2024-333876
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 GSE239775_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 PRJNA1000950 and SRA study SRP452972. Searching any of these in the dataset finder brings you back here.

Study design
1177 samples, each with a distinct title — no replicated groups

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

How we read this: Read from the first 400 of 1177 sample titles: 400 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

+ 1137 more — browse all 1177 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.