Intraindividual epigenetic heterogeneity underlying phenotypic subtypes of advanced prostate cancer [RNA-seq]
RNA-seq (gene expression) · human · 98 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
- 98 samples: 98 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
- Intraindividual epigenetic heterogeneity underlying phenotypic subtypes of advanced prostate cancerNature communications · 2025
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 GSE289466_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: 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 PRJNA1223173 and SRA study SRP563639. 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 98 sample titles: 98 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.
- GSM8791840 CA0046_Z1, RNA-seq
- GSM8791841 CA0046_Z2, RNA-seq
- GSM8791842 CA0046_Z3, RNA-seq
- GSM8791843 CA0090_Z1, RNA-seq
- GSM8791844 CA0090_Z2, RNA-seq
- GSM8791845 CA0090_Z3, RNA-seq
- GSM8791846 CA0090_Z4, RNA-seq
- GSM8791847 CA0090_Z5, RNA-seq
- GSM8791848 CA0090_Z6, RNA-seq
- GSM8791849 DFCI16_Z1, RNA-seq
- GSM8791850 DFCI19_Z1, RNA-seq
- GSM8791851 DFCI20_Z1, RNA-seq
- GSM8791852 DFCI20_Z2, RNA-seq
- GSM8791853 DFCI20_Z3, RNA-seq
- GSM8791854 DFCI23_Z1, RNA-seq
- GSM8791855 DFCI23_Z2, RNA-seq
- GSM8791856 DFCI23_Z3, RNA-seq
- GSM8791857 DFCI24_Z1, RNA-seq
- GSM8791858 DFCI24_Z2, RNA-seq
- GSM8791859 DFCI24_Z3, RNA-seq
- GSM8791860 DFCI46_Z1, RNA-seq
- GSM8791861 DFCI46_Z2, RNA-seq
- GSM8791862 DFCI46_Z3, RNA-seq
- GSM8791863 DFCI46_Z4, RNA-seq
- GSM8791864 DFCI46_Z5, RNA-seq
- GSM8791865 DFCI53_Z1, RNA-seq
- GSM8791866 DFCI53_Z2, RNA-seq
- GSM8791867 DFCI53_Z3, RNA-seq
- GSM8791868 WCM0_1, RNA-seq
- GSM8791869 WCM0_2, RNA-seq
- GSM8791870 WCM0_3, RNA-seq
- GSM8791871 WCM0_4, RNA-seq
- GSM8791872 WCM0_LM1A, RNA-seq
- GSM8791873 WCM0_PM2, RNA-seq
- GSM8791874 WCM1024_Z1, RNA-seq
- GSM8791875 WCM1070_Z4, RNA-seq
- GSM8791876 WCM1070_Z5, RNA-seq
- GSM8791877 WCM1070_Z6, RNA-seq
- GSM8791878 WCM1070_Z7, RNA-seq
- GSM8791879 WCM1070_Z8, RNA-seq
+ 58 more — browse all 98 samples with per-sample file links →
- GSE289467 Intraindividual epigenetic heterogeneity underlying phenotypic subtypes of advanced prostate cancer [CUT&Tag] 50 samples shares intraindividual, heterogeneity, epigenetic, underlying, phenotypic, subtypes, advanced, prostate
- GSE281743 Epigenetic Subtypes of High-Grade T1 Bladder Cancer Reveal Intra-Tumor Heterogeneity and Distinct Interactions with Tumor Microenvironment 41 samples shares heterogeneity, epigenetic, subtypes
- GSE302273 The evolution and heterogeneity of lethal metastatic bladder cancer subtypes 89 samples shares heterogeneity, subtypes
- GSE316337 Multi-omics profiling reveals microbiota, metabolite, lipid, and immunological heterogeneity underlying distinct pathophysiological mechanisms of age-related endotypes in type 1 diabetes 54 samples shares heterogeneity, underlying
- GSE324131 A single-cell and spatial atlas of prostate cancer reveals the combinatorial nature of gene modules underlying lineage plasticity and metastasis 38 samples shares underlying, prostate
- GSE280639 Multichrome encoding-based multiplexed, spatially resolved imaging reveals single-cell RNA epigenetic modifications heterogeneity 21 samples shares heterogeneity, epigenetic
- GSE316497 Genotype-Epigenome-Phenotype Integration Reveals the Contributions of Peripheral Immune Cells to Bipolar Disorder Pathogenesis, Phenotypic Heterogeneity, and Therapy 1012 samples shares heterogeneity, phenotypic
- GSE302930 Epigenetic Atlas of Bladder Cancer Reveals Master Transcription Factors and Risk-Associated Regulatory Elements in Luminal and Basal-Squamous Molecular Subtypes 92 samples shares epigenetic, subtypes
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.