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Single-cell mapping of human endometrium and decidua reveals epithelial and stromal contributions to fertility [single cell RNA-seq]

GSE290822 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2025/11/24 Platform GPL18573
At a glance

Single-cell RNA-seq · human · 15 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
15 samples: 4 × endometrium, early secretory, vs 4 × endometrium, mid secretory, vs 3 × endometrium, late secretory, vs 3 × endometrium, first trimester decidua,Groups 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
Single-cell mapping of human endometrium and decidua reveals epithelial and stromal contributions to fertilityJCI insight · 2026
Summary (written by the submitters)
Embryo implantation relies on the development of a receptive endometrium during the secretory phase of the menstrual cycle. Prior studies have attempted to define the window of embryo implantation within the secretory phase based on patterns of differentially expressed genes, but consensus surrounding this signature has not been achieved. We aim to examine the cell types that characterize the purported receptivity signature and identify new transcriptomic markers that define the mid-secretory endometrium through integrated bulk and single-cell RNA sequencing.
Published in
Single-cell mapping of human endometrium and decidua reveals epithelial and stromal contributions to fertility
Burns GW, Paul EN, Persaud M et al. · JCI insight 2026 · PMID 41574608 · doi:10.1172/jci.insight.195254
This dataset
Open GSE290822 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 GSE290822_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 PRJNA1230176 and SRA study SRP567168. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41574608) ↗
Study design
4 × endometrium, early secretory, vs 4 × endometrium, mid secretory, vs 3 × endometrium, late secretory, vs 3 × endometrium, first trimester decidua,

Supports a between-group comparison across 14 samples.

How we read this: 4 replicated groups read from 15 sample titles; they account for 14 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.