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Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells (scRNA-seq)

GSE227108 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2024/06/14 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 18 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)
Samples
18 samples: 18 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
Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cellsCell stem cell · 2024
Summary (written by the submitters)
Understanding prostate response to castration and androgen receptor signaling inhibitors (ARSI) is critical to improving long-term prostate cancer (PCa) patient survival. Here we use a multi-omics approach on 229,794 single cells to create a mouse single-cell reference atlas better suited to interpreting mouse prostate biology and castration response.
Read the full summary ↓
Our reference atlas refines single-cell annotations and provides chromatin context, which, when coupled with mouse lineage tracing demonstrates that the castration-resistant luminal cells are distinct from the pre-existent urethra-proximal stem/progenitor cells. Molecular pathway analysis and therapeutic studies further implicate JUN/FOS, WNT/b-Catenin, FOXQ1, NFkB, and JAK/STAT pathways as the major drivers of castration-resistant luminal populations with high relevance to human PCa. Importantly, we demonstrate the utility of our datasets, which can be explored through an interactive portal (https://visportal.roswellpark.org/data/tang/), to aid in developing novel combination treatments with ARSI for advanced PCa patients.
Published in
Integrated single-cell analysis defines the epigenetic basis of castration-resistant prostate luminal cells
Kirk JS, Wang J, Long M et al. · Cell stem cell 2024 · PMID 38878775 · doi:10.1016/j.stem.2024.05.008
This dataset
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.

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 GSE227108_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA943237 and SRA study SRP426644. Searching any of these in the dataset finder brings you back here.

Study design
18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 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
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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.