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Identifying clones in myelodysplastic syndromes by using single-cell RNA sequencing

GSE293014 Homo sapiens (human) Single-cell RNA-seq 11 samples Submitted 2026/03/21 Platform GPL21697
At a glance

Single-cell RNA-seq · human · 11 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)
Topic
Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples
11 samples: 11 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
Identifying Clones in Myelodysplastic Syndromes by Using Single-Cell RNA SequencingHematological oncology · 2026
Summary (written by the submitters)
We employed single-cell RNA sequencing to sequence hematopoietic stem cells (HSC) derived from bone marrow aspirations of seven patients with myelodysplastic syndrome (MDS) and four control subjects. Based on gene expression and pathway-enrichment analyses, we inferred chromosomal Y deletion and characterized the transcriptome of chromosome Y-deleted HSC in comparison to chromosomally intact HSC. Our results support the premise that chromosome Y deletion is not a benign aging phenomenon and highlight the importance of upregulation of the anti-apoptotic pathway in the pathogenesis of MDS.
Published in
Identifying Clones in Myelodysplastic Syndromes by Using Single-Cell RNA Sequencing
Pollak R, Ner-Gaon H, Olender L et al. · Hematological oncology 2026 · PMID 41886772 · doi:10.1002/hon.70189
This dataset
Open GSE293014 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 GSE293014_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 PRJNA1242351. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41886772) ↗
Study design
11 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 11 sample titles: 11 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
More Myelodysplastic syndromes datasets

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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.