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Single-cell transcriptomic atlas of adult dermatomyositis, cutaneous lupus erythematosus and healthy skin

GSE334588 Homo sapiens (human) Single-cell RNA-seq 48 samples Submitted 2026/06/08 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 48 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)
Samples
48 samples: 6 conditions, mostly in duplicateGroups 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)
Adult-onset dermatomyositis (DM) is a systemic autoimmune disease associated with an elevated risk of malignancy, yet the cellular and molecular features distinguishing cancer-associated DM from non-cancer DM remain poorly defined. Here, we conduct a comprehensive single-cell RNA sequencing analysis of adult-onset DM skin, including lesional and non-lesional samples, alongside cutaneous lupus erythematosus (CLE) and healthy control skin, to characterize immune and stromal cell states and disease-specific transcriptional programs.
Read the full summary ↓
We identify distinct immune-stromal cell populations that differentiate cancer-associated DM from non-cancer-associated DM and CLE, including a vascular injury phenotype with hypoxia and metabolic reprogramming enriched in cancer-associated DM. These findings nominate cell-state-defining molecular features as potential biomarkers for cancer screening and therapeutic targeting in adult dermatomyositis.
This dataset
Open GSE334588 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 GSE334588_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 PRJNA1475987 and SRA study SRP707581. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in duplicate
Dermatomyositis lesional skin, DM ×22 Cutaneous lupus erythematosus lesional skin, … ×9 Cutaneous lupus erythematosus non-lesional sk… ×6 Healthy control skin, H1 ×4 Healthy control skin, H2 ×2 Dermatomyositis non-lesional skin, NL_DM ×2 Healthy control skin, H3 ×1 Healthy control skin, H4 ×1 +1 more

Supports a case/control comparison: 39 samples read as cases, 9 as controls.

How we read this: 6 replicated groups read from 48 sample titles; they account for 45 of them. 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.