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ETMR stem-like state and chemo-resistance are supported by perivascular cells at single-cell resolution

GSE224478 Homo sapiens (human) Single-cell RNA-seq 51 samples Submitted 2025/04/16 Platform GPL30172Platform GPL30173Platform GPL19057Platform GPL18573Platform GPL30202
At a glance

Single-cell RNA-seq · human · 51 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
51 samples: 43 distinct titles, 6 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
ETMR stem-like state and chemo-resistance are supported by perivascular cells at single-cell resolutionNature communications · 2025
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
ETMR stem-like state and chemo-resistance are supported by perivascular cells at single-cell resolution
de Faria FW, Riedel NC, Münter D et al. · Nature communications 2025 · PMID 40562749 · doi:10.1038/s41467-025-60442-9
This dataset
Open GSE224478 in finder → Find more 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 GSE224478_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 PRJNA931303 and SRA study SRP424148. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40562749) ↗
Study design
43 distinct titles, 6 of them repeated
CatSmo51_embryo ×3 KK22-H ×3 Murine E16.5 cre + ×2 Murine E16.5 cre ×2 ETMR-monoculture ×2 ETMR-PC culture ×2

Supports a case/control comparison: 1 samples read as cases, 9 as controls.

How we read this: Read from 51 sample titles: 43 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

+ 11 more — browse all 51 samples with per-sample file links →

Datasets on a similar topic

Search all 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.