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Multi-omics data analysis for the JGOG3025-TR2 ovarian cancer cohort [RNA-seq]

GSE263083 Homo sapiens (human) RNA-seq (gene expression) 291 samples Submitted 2024/08/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 291 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
291 samples: 291 × ovarian cancer PGroups 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
Molecular classification of ovarian high-grade serous/endometrioid carcinomas through multi-omics analysis: JGOG3025-TR2 studyBritish journal of cancer · 2024
Summary (written by the submitters)
The JGOG3025 study was conducted by the Japanese Gynecologic Oncology Group (JGOG) on 710 patients with epithelial ovarian cancer (NCT03159572). In the JGOG3025-TR2 study, fresh frozen tumor tissues from 274 and 15 cases diagnosed as stage II or higher high-grade serous carcinoma (HGSC) or high-grade endometrioid carcinoma (HGEC) in the central pathological review were submitted to SNP array, total RNA-sequencing, and DNA methylation array analyses.
Published in
Molecular classification of ovarian high-grade serous/endometrioid carcinomas through multi-omics analysis: JGOG3025-TR2 study
Takamatsu S, Hillman RT, Yoshihara K et al. · British journal of cancer 2024 · PMID 39215190 · doi:10.1038/s41416-024-02837-x
This dataset
Open GSE263083 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 GSE263083_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1092599 and SRA study SRP498348. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39215190) ↗
Study design
291 × ovarian cancer P

Supports a between-group comparison across 291 samples.

How we read this: 1 replicated groups read from 291 sample titles; they account for 291 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

+ 251 more — browse all 291 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.