A Living Organoid Biobank of Crohn’s Disease Patients Reveals Distinct Clinical Correlates of Molecular Subtypes of Disease
RNA-seq (gene expression) · human · 24 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
- 24 samples
- 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
- New approach methodologies in Crohn's disease link molecular disease subtypes to clinical outcomesAmerican journal of physiology. Gastrointestinal and liver physiology · 2026
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 GSE293539_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 PRJNA1244902 and SRA study SRP575736. Searching any of these in the dataset finder brings you back here.
The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Sample titles run CD32 … CD68 and carry no group information.
- GSM8884824 CD32
- GSM8884825 CD35
- GSM8884826 CD42
- GSM8884827 CD58
- GSM8884828 CD61
- GSM8884829 CD69
- GSM8884830 CD74
- GSM8884831 CD30
- GSM8884832 CD47
- GSM8884833 CD59
- GSM8884834 CD60
- GSM8884835 CD11
- GSM8884836 CD24
- GSM8884837 CD50
- GSM8884838 CD52
- GSM8884839 CD63
- GSM8884840 CD27
- GSM8884841 CD21
- GSM8884842 CD28
- GSM8884843 CD26
- GSM8884844 CD20
- GSM8884845 CD19
- GSM8884846 CD23
- GSM8884847 CD68
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- GSE319130 Multi-omic analysis reveals molecular subtypes with distinct immunological phenotypes in SLE [RNA-Seq] 804 samples shares distinct, subtypes
- GSE318816 Blood-based Molecular Endotyping of Fibrotic Hypersensitivity Pneumonitis Identifies Two Immune Subtypes with Divergent Clinical Outcomes 126 samples shares clinical, subtypes
- GSE267010 A consensus molecular subtypes classification strategy for clinical colorectal cancer tissues 104 samples shares clinical, subtypes
- GSE233236 Pan-Cancer Single-Cell Dissection Reveals Phenotypically Distinct B Cell Subtypes 78 samples shares distinct, subtypes
- GSE309967 Immunometabolic Endotypes Define Distinct Clinical Trajectories in Type 2 Diabetes 48 samples shares distinct, clinical
- GSE309941 Immunometabolic Endotypes Define Distinct Clinical Trajectories in Type 2 Diabetes [bulk RNA-seq] 42 samples shares distinct, clinical
- GSE246215 Cross-tissue human fibroblast atlas reveals myofibroblast subtypes with distinct roles in immune modulation [scRNA-seq] 38 samples shares distinct, 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.