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Risk assessment with gene expression markers in sepsis development

GSE208587 Homo sapiens (human) RNA-seq (gene expression) 61 samples Submitted 2024/08/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 61 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
61 samples: 61 × BX0279Groups 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
Risk assessment with gene expression markers in sepsis developmentCell reports. Medicine · 2024
Summary (written by the submitters)
We investigated the individual phenotypic predisposition to developing uncomplicated infection or sepsis in a large cohort of non-infected patients undergoing major elective surgery. We built machine learning classification models on preoperative transcriptomic signatures to predict postoperative outcomes including sepsis. To test the predictive capability of these models for ongoing infection, whole blood RNA sequencing analysis on 61 independent patients with COVID-19 (10 mild, 51 severe cases) was performed.
Published in
Risk assessment with gene expression markers in sepsis development
Garcia Lopez A, Schäuble S, Sae-Ong T et al. · Cell reports. Medicine 2024 · PMID 39232497 · doi:10.1016/j.xcrm.2024.101712
This dataset
Open GSE208587 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE208587_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA860181 and SRA study SRP387110. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39232497) ↗
Study design
61 × BX0279

Supports a between-group comparison across 61 samples.

How we read this: 1 replicated groups read from 61 sample titles; they account for 61 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

+ 21 more — browse all 61 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.