Colon tissue gene expression associated with vedolizumab treatment effectiveness in ulcerative colitis.
RNA-seq (gene expression) · human · 60 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
- 60 samples: 60 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
- Intestinal transcriptomic analysis and prediction of biomarkers associated with mucosal healing following vedolizumab treatment in ulcerative colitis using machine learningBMC gastroenterology · 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 GSE282580_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 PRJNA1189171 and SRA study SRP546867. 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 60 sample titles: 60 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.
- GSM8646415 subject 1, inf, 0W
- GSM8646416 subject 1, non-inf, 0W
- GSM8646417 subject 1, inf, 14W
- GSM8646418 subject 1, non-inf, 14W
- GSM8646419 subject 1, inf, 54W
- GSM8646420 subject 1, non-inf, 54W
- GSM8646421 subject 2, inf, 0W
- GSM8646422 subject 2, non-inf, 0W
- GSM8646423 subject 2, inf, 14W
- GSM8646424 subject 2, non-inf, 14W
- GSM8646425 subject 2, inf, 54W
- GSM8646426 subject 2, non-inf, 54W
- GSM8646427 subject 3, inf, 0W
- GSM8646428 subject 3, non-inf, 0W
- GSM8646429 subject 3, inf, 14W
- GSM8646430 subject 3, non-inf, 14W
- GSM8646431 subject 3, inf, 54W
- GSM8646432 subject 3, non-inf, 54W
- GSM8646433 subject 4, inf, 0W
- GSM8646434 subject 4, non-inf, 0W
- GSM8646435 subject 4, inf, 14W
- GSM8646436 subject 4, non-inf, 14W
- GSM8646437 subject 4, inf, 54W
- GSM8646438 subject 4, non-inf, 54W
- GSM8646439 subject 5, inf, 0W
- GSM8646440 subject 5, non-inf, 0W
- GSM8646441 subject 5, inf, 14W
- GSM8646442 subject 5, non-inf, 14W
- GSM8646443 subject 5, inf, 54W
- GSM8646444 subject 5, non-inf, 54W
- GSM8646445 subject 6, inf, 0W
- GSM8646446 subject 6, non-inf, 0W
- GSM8646447 subject 6, inf, 14W
- GSM8646448 subject 6, non-inf, 14W
- GSM8646449 subject 6, inf, 54W
- GSM8646450 subject 6, non-inf, 54W
- GSM8646451 subject 7, inf, 0W
- GSM8646452 subject 7, non-inf, 0W
- GSM8646453 subject 7, inf, 14W
- GSM8646454 subject 7, non-inf, 14W
+ 20 more — browse all 60 samples with per-sample file links →
- GSE224758 Gene expression profiling of colon biopsies from ulcerative colitis patients and healthy volunteers 22 samples shares ulcerative, colitis, colon
- GSE243625 Inflammatory transcriptomic signatures and cell type compositions in inflamed and non-inflamed colonic mucosa of ulcerative colitis 45 samples shares ulcerative, colitis, colon
- GSE334803 RNA sequencing of colonic tissues from ulcerative colitis patients and healthy controls 12 samples shares ulcerative, colitis, colon
- GSE190564 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - whole tissue scRNA-Seq 62 samples shares ulcerative, colitis
- GSE245890 Analysis of rectal transcriptome in ulcerative colitis (UC) patients who received tofacitinib 51 samples shares ulcerative, colitis
- GSE288617 Paired transcriptomics reveals similarities between cytokine-stimulated organoids and ulcerative colitis epithelial responses 41 samples shares ulcerative, colitis
- GSE284191 Pathogenesis elucidation of Ulcerative Colitis Focusing on Appendix Immunity 27 samples shares ulcerative, colitis
- GSE253006 Differential effects of tofacitinib on macrophage activation contribute to lack of response in ulcerative colitis patients 23 samples shares ulcerative, colitis
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.