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Multiomics Analyses Unveil Immune Landscape in Pediatric and Adult Sepsis [scRNA_seq]

GSE279452 Homo sapiens (human) Single-cell RNA-seq 266 samples Submitted 2025/09/28 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 266 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
266 samples: 147 distinct titles, 12 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.
Summary (written by the submitters)
Sepsis is a leading cause of global mortality, characterized by organ dysfunction due to a dysregulated immune response to infection. This study aims to delineate the immune landscape in sepsis through single-cell RNA sequencing (scRNA-seq). A total of 133 samples were analyzed, including PBMCs from healthy adults, adult ICU controls, adult sepsis patients, healthy children, pediatric ICU controls, and pediatric sepsis patients.
Read the full summary ↓
The scRNA-seq analysis revealed both common and unique immune cell populations across different infection sources and between adults and children. These findings provide insights into the pathophysiology of sepsis and suggest potential targets for personalized therapeutic approaches.
This dataset
Open GSE279452 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 GSE279452_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: 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 PRJNA1172727. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
147 distinct titles, 12 of them repeated
scRNA Abd-S ×36 scRNA Res-S ×32 scRNA Abd-PS ×9 scRNA Uri-S ×9 scRNA IC ×8 scRNA HC ×7 scRNA Res-PS ×7 scRNA Skin-S ×7 +4 more

How we read this: Read from 266 sample titles: 147 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

+ 226 more — browse all 266 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.