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GSE266608 Mus musculus (mouse) Single-cell RNA-seq 63 samples Submitted 2025/10/21 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 63 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
63 samples: 63 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.
Summary (written by the submitters)
Multipotent hematopoietic progenitors with coherent developmental transcriptional programs are defined by their ability to give rise to distinct cell lineages. While the identification of multilineage progenitors is aided by single-cell technologies, new techniques are required for their rigorous delineation and isolation. We describe a new approach to dissect and contrast well-defined and newly proposed immunophenotypically defined hematopoietic progenitors using integrative multimodal single-cell genomics and linked high-dimensional flow cytometry.
Read the full summary ↓
The lineage potential of implicated multi-lineage progenitors could be resolved through their sequential isolation, lineage tracing, genetic reporters, in vitro differentiation and gene-regulatory prediction analyses. These analyses implicate coordinated transcription factors operating on composite elements for distinct multilineage cell states. A newly identified precursor of the neutrophil-monocytic bipotential (MultiLin-1) was confirmed to be transcriptionally reprogrammed by Th2 cytokines following infection, to produce the successive waves of neutrophils, basophils and eosinophils. This work supports a stepwise model of hematopoiesis in which lineage transitions occur as discrete, isolatable cell states.
This dataset
Open GSE266608 in finder → Find more mouse 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 GSE266608_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 PRJNA1107950 and SRA study SRP505769. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
63 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 63 sample titles: 63 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

+ 23 more — browse all 63 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.