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Gene expression profile at single cell level of cells isolated from the bone fracture gap and un-injured bone marrow in mouse osteotomy models

GSE230260 Mus musculus (mouse) Single-cell RNA-seq 15 samples Submitted 2025/02/14 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 15 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
15 samples: 15 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
Erythroid precursors regulate local oxygen tension and repair outcomes in the bone marrow nichebioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
We investigated the cell composition in the bone fracture (osteotomy) gap under two different ambulatory loading conditions (stiif vs. compliant - external fixator). In addition, we applied an receptor inhibitor or respective isotype control to understand the role of a specific progenitor subpopulation during the onset of bone fracture repair. Un-injured bone marrow was used as control. Some samples were combined prior to library prep as indicated in the sample titles
Published in
Erythroid precursors regulate local oxygen tension and repair outcomes in the bone marrow niche
Lang A, Collins JM, Nijsure MP et al. · bioRxiv : the preprint server for biology 2025 · PMID 39829797 · doi:10.1101/2025.01.10.632440
This dataset
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.

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 GSE230260_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA958141 and SRA study SRP433736. Searching any of these in the dataset finder brings you back here.

Study design
15 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 15 sample titles: 15 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
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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.