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Human Skeletal Stem Cell Diversity

GSE233970 Homo sapiens (human) Single-cell RNA-seq 34 samples Submitted 2025/02/25 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 34 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
34 samples: 34 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
Human skeletal development and regeneration are shaped by functional diversity of stem cells across skeletal sitesCell stem cell · 2025
Summary (written by the submitters)
We have used SmartSeq2 to sequence single phenotypic human skeletal stem cell (SSCs) and downstream lineage populations purified via FACS from fetal skeletal tissues and patient specimens. SSC populations were isolated based on their previously reported surface marker profiles. A human SSC (CD45-CD235a-CD31-TIE2-CD146-PDPN+CD73+CD164+), a human bone-cartilage-stroma-progenitor (BCSP; CD45-CD235a-CD31-TIE2-CD146+PDPN+) and an osteoprogenitor (OP; CD45-CD235a-CD31-TIE2-CD146+PDPN-) were investigated.
Published in
Human skeletal development and regeneration are shaped by functional diversity of stem cells across skeletal sites
Ambrosi TH, Taheri S, Chen K et al. · Cell stem cell 2025 · PMID 40118065 · doi:10.1016/j.stem.2025.02.013
This dataset
Open GSE233970 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 GSE233970_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 PRJNA979132 and SRA study SRP440923. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40118065) ↗
Study design
34 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 34 sample titles: 34 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

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.