← BioTransfer GEO Dataset Finder
GEO series

Comprehensive analysis of Bulk RNA-seq and Single-nuclei RNA-seq reveals the origin of high-grade serous “ovarian” carcinoma [snRNA-seq]

GSE270250 Homo sapiens (human) Single-nucleus RNA-seq 13 samples Submitted 2025/06/30 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 13 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Homo sapiens (human)
Topic
Ovarian cancerThis series is part of our curated briefing on it.
Samples
13 samples: 4 × Epithelial ovarian cancer, vs 3 × Isthmus, vs 3 × Ampulla, vs 3 × Fimbriae,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.
Summary (written by the submitters)
High grade serous ovarian cancer (HGSOC) is characterized by late stage, rapid progression, easy drug resistance, high mortality and recurrence rate.Tubal secretory cells have always been considered as the origin cells of HGSOC,due to the high heterogeneity of the latter,the type and mechanism of cell origin is poorly confirmed.Combined with single-nuclei RNA sequencing(snRNA-seq) and Bulk tissue transcriptome sequencing,we expounded the composition of epithelial cell subgroups of fallopian tubes and HGSOCs.
This dataset
Open GSE270250 in finder → Find more human RNA-seq datasets → Ovarian cancer 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 GSE270250_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 PRJNA1125874 and SRA study SRP514837. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × Epithelial ovarian cancer, vs 3 × Isthmus, vs 3 × Ampulla, vs 3 × Fimbriae,

Supports a between-group comparison across 13 samples.

How we read this: 4 replicated groups read from 13 sample titles; they account for 13 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
More Ovarian cancer datasets

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.