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A reference model for circulating hematopoietic stem cells with applications to diagnostics

GSE285943 Homo sapiens (human) Single-cell RNA-seq 299 samples Submitted 2025/01/06 Platform GPL24676Platform GPL34284Platform GPL34762Platform GPL34281
At a glance

Single-cell RNA-seq · human · 299 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)
Topic
Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples
299 samples: 299 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
A reference model of circulating hematopoietic stem cells across the lifespan with applications to diagnosticsNature medicine · 2025
Summary (written by the submitters)
With aging, deviation of human blood counts from their normal range accompanies the transition from health to hematological and other diseases. Hematopoietic stem and progenitor cells (HSPCs) deliver life-long multi-lineage output, but their variation across healthy humans and their diagnostic utility haven’t been characterized. To address this, we introduce an HSPC reference model using single-cell profiling of circulating CD34+ cells (cHSPCs) from 148 healthy individuals.
Read the full summary ↓
We characterize physiological cHSPC composition, link it with standard blood counts and show that the ratio between lymphoid and myeloid progenitors is decreased in ageing males. Using this new reference model, we develop sensitive tools which could be used for diagnostics of myelodysplastic syndrome (MDS) from peripheral blood without bone marrow analysis. Profiling cHSPC compositions leads to the discovery of new MDS subclasses, ranging in their lymphocyte, basophil and granulocyte progenitor frequencies. The data and methodologies presented herein highlight the role of reference modeling in promoting clinical applications of single-cell genomics in MDS and in the future for other diseases too. This dataset can be explored as metacells at https://apps.tanaylab.com/MCV/blood_aging (for more about metacells, see https://github.com/tanaylab/metacells and https://doi.org/10.1186/s13059-022-02667-1).
Published in
A reference model of circulating hematopoietic stem cells across the lifespan with applications to diagnostics
Furer N, Rappoport N, Milman O et al. · Nature medicine 2025 · PMID 40579545 · doi:10.1038/s41591-025-03716-5
This dataset
Open GSE285943 in finder → Find more human RNA-seq datasets → Myelodysplastic syndromes landscape →
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 GSE285943_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 PRJNA1207024. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40579545) ↗
Study design
299 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 299 sample titles: 299 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

+ 259 more — browse all 299 samples with per-sample file links →

More Myelodysplastic syndromes datasets

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.