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Gene expression analysis of corneal endothelial cells in iridocorneal endothelial syndrome

GSE256242 Homo sapiens (human) Single-cell RNA-seq 19 samples Submitted 2026/01/12 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 19 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)
Samples
19 samples: 6 conditions, mostly in triplicateGroups 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
Etiology of Iridocorneal Endothelial Syndrome: Viral Infection and Immune SuppressionCornea · 2026
Summary (written by the submitters)
Iridocorneal endothelial (ICE) syndrome is a rare ocular disease affecting the anterior segment, characterized by progressive deterioration leading to significant complications, including corneal endothelial compensation and secondary glaucoma. The unclear etiology of this syndrome limits clinical management to symptomatic interventions.
Read the full summary ↓
The abnormality of corneal endothelial cells (ICE cells) in patients with ICE syndrome is considered the initial step of this disease. This study endeavors to elucidate the transcriptomic profiles of ICE cells utilizing smart-seq2 single-cell RNA sequencing techniques.
Published in
Etiology of Iridocorneal Endothelial Syndrome: Viral Infection and Immune Suppression
Zhang J, Yuan B, Peng R et al. · Cornea 2026 · PMID 40526465 · doi:10.1097/ICO.0000000000003911
This dataset
Open GSE256242 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 GSE256242_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 PRJNA1078767 and SRA study SRP490714. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40526465) ↗
Study design
6 conditions, mostly in triplicate
Normal_sample3 ×4 ICE_sample3 ×4 Normal_sample1 ×3 ICE_sample1 ×3 ICE_sample2 ×3 Normal_sample2 ×2

Supports a between-group comparison across 19 samples.

How we read this: 6 replicated groups read from 19 sample titles; they account for 19 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
Datasets on a similar topic

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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.