GEO series

Single-Cell RNA Sequencing of the Human Endometrium in Healthy Controls and Patients with Polycystic Ovary Syndrome

GSE333241 Homo sapiens (human) Single-cell RNA-seq 2 samples Submitted 2026/07/22 Platform GPL18573

At a glance

Single-cell RNA-seq · human · 2 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: 2 samples
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)

Polycystic ovary syndrome (PCOS) is a common endocrine disorder affecting reproductive-aged women and is associated with endometrial dysfunction, including reduced receptivity, increased miscarriage risk, and elevated endometrial cancer risk. However, the cellular and molecular heterogeneity of the endometrium in PCOS patients remains poorly understood.

Read the full summary ↓

In this study, we performed single-cell RNA sequencing (scRNA-seq) on endometrial biopsies obtained from healthy control women and PCOS patients. Endometrial samples were collected during the proliferative phase. We analyzed endometrial cell composition and transcriptional profiles at single-cell resolution. Our findings reveal PCOS-specific alterations in endometrial cell type composition, as well as cell-type-specific gene expression changes associated with inflammation, progesterone resistance, and extracellular matrix remodeling. These results provide a comprehensive cellular atlas of the PCOS endometrium and identify potential molecular targets for future therapeutic intervention.

This dataset

Open GSE333241 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 GSE333241_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 PRJNA1470571 and SRA study SRP703681. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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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.