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Transcriptional stratification of necrotizing enterocolitis identifies distinct disease subtypes

GSE297483 Homo sapiens (human) RNA-seq (gene expression) 23 samples Submitted 2025/05/19 Platform GPL24676Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 23 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
23 samples: 21 distinct titles, 1 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.
Paper
Transcriptional stratification of necrotizing enterocolitis identifies distinct disease subtypesScientific reports · 2026
Summary (written by the submitters)
Necrotizing enterocolitis (NEC) is a severe inflammatory disorder of the intestine that affects neonatal babies, with a mortality rate of 30–50%. Despite the severe nature of the disease, its rare incidence and early onset prevent further understanding of its etiology and the development of treatment strategies. To further understand the pathogenic mechanism of this disease, we subjected intestinal tissues from ten NEC patients and three control individuals to RNA-sequencing.
Read the full summary ↓
Clustering of the affected tissues revealed three clusters, each with a distinct transcriptional profile characterized by the expression of genes enriched in inflammatory pathways related to lipid binding and no obvious expression signature. The three subtypes displayed distinct gene expression patterns specific to the cell types composing the small intestine layers. Our results elucidate the genetic rationale underlying patient-specific symptoms, prognosis.
Published in
Transcriptional stratification of necrotizing enterocolitis identifies distinct disease subtypes
Lee J, Nam SH, Ko D et al. · Scientific reports 2026 · PMID 41519836 · doi:10.1038/s41598-025-17104-z
This dataset
Open GSE297483 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 GSE297483_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 PRJNA1261244 and SRA study SRP584323. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41519836) ↗
Study design
21 distinct titles, 1 of them repeated
Stormal reversal surgery neonates tissue from… ×3

How we read this: Read from 23 sample titles: 21 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
Datasets on a similar topic

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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.