Gene expression profile at single cell level of ovarian clear cell carcinoma (OCCC) [snRNA-seq OCCC]
Single-nucleus RNA-seq · human · 10 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)
- Samples
- 10 samples: 10 samples, each with a distinct title — no replicated groupsGroups 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
- Targeting PDGF signaling of cancer-associated fibroblasts blocks feedback activation of HIF-1α and tumor progression of clear cell ovarian cancerCell reports. Medicine · 2024
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE224334_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA930669 and SRA study SRP420635. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 10 sample titles: 10 distinct titles with little repetition. 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.
- GSM7019825 OCCR1, snRNAseq
- GSM7019826 OCCR2, snRNAseq
- GSM7019827 OCCR3, snRNAseq
- GSM7019828 OCCR4, snRNAseq
- GSM7019829 OCCR5, snRNAseq
- GSM7019830 OCCS1, snRNAseq
- GSM7019831 OCCS2, snRNAseq
- GSM7019832 OCCS3, snRNAseq
- GSM7019833 OCCS4, snRNAseq
- GSM7019834 OCCS5, snRNAseq
- GSE273637 Gene expression profiles of platinum-resistant high-grade serous ovarian carcinoma 20 samples shares ovarian
- GSE213452 Gene expression profile at single cell level of cells from cholangiocarcinoma(CCA) and adjacent tissues. 11 samples shares level
- GSE308103 Single-nucleus RNA-sequencing (snRNA-seq) analysis of normal lung tissues, precursor lung lesions and invasive lung adenocarcinomas 75 samples shares snrna-seq
- GSE285827 PARP inhibitors differentially regulate immune responses in distinct genetic backgrounds of high-grade serous tubo-ovarian carcinoma 18 samples shares ovarian
- GSE324929 RNA-seq analysis of FDX2-inducible knockout (FDX2-iKO) ES2 ovarian carcinoma cells under normoxic and hypoxic conditions 12 samples shares ovarian
- GSE254569 Gene expression profiles at single-cell level of human post-mortem brain tissue from the orbitofrontal cortex 92 samples shares level
- GSE290927 Gene expression profile at single cell level of human laryngeal normal, preneoplastic and tumorigenic states 40 samples shares level
- GSE269936 Gene expression profile at single cell level for human metastatic melanoma samples 38 samples shares level
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.