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Single-cell gene programs define subtype identity and metastatic trajectories in renal cell carcinoma

GSE328692 Mus musculus (mouse) Single-cell RNA-seq 34 samples Submitted 2026/07/20 Platform GPL28038Platform GPL25431Platform GPL31277Platform GPL24676Platform GPL25526Platform GPL33484
At a glance

Single-cell RNA-seq · mouse · 34 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Topic
Kidney cancerThis series is part of our curated briefing on it.
Samples
34 samples: 26 distinct titles, 4 of them repeatedGroups 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.
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
This dataset
Open GSE328692 in finder → Find more RNA-seq datasets → Kidney 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 GSE328692_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 PRJNA1456136 and SRA study SRP693112. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
26 distinct titles, 4 of them repeated
Bulk_RNA-seq_siControl ×3 Bulk_RNA-seq_siHIF1A ×3 Bulk_RNA-seq_siHIF1A_siHIF2A ×3 Bulk_RNA-seq_siHIF2A ×3

How we read this: Read from 34 sample titles: 26 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.

Samples in this study
More Kidney cancer datasets

Search all RNA-seq datasets in GEO →

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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.