RNA sequencing of colonic tissues from ulcerative colitis patients and healthy controls
RNA-seq (gene expression) · human · 12 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
- 12 samples: 12 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.
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 GSE334803_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 PRJNA1476509 and SRA study SRP708005. 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 12 sample titles: 12 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.
- GSM9797392 Healthy control, replicate 1, RNA_seq
- GSM9797393 Healthy control, replicate 2, RNA_seq
- GSM9797394 Healthy control, replicate 3, RNA_seq
- GSM9797395 Healthy control, replicate 4, RNA_seq
- GSM9797396 Healthy control, replicate 5, RNA_seq
- GSM9797397 Healthy control, replicate 6, RNA_seq
- GSM9797398 Ulcerative colitis, replicate 1, RNA_seq
- GSM9797399 Ulcerative colitis, replicate 2, RNA_seq
- GSM9797400 Ulcerative colitis, replicate 3, RNA_seq
- GSM9797401 Ulcerative colitis, replicate 4, RNA_seq
- GSM9797402 Ulcerative colitis, replicate 5, RNA_seq
- GSM9797403 Ulcerative colitis, replicate 6, RNA_seq
- GSE224758 Gene expression profiling of colon biopsies from ulcerative colitis patients and healthy volunteers 22 samples shares ulcerative, colitis, healthy
- GSE243625 Inflammatory transcriptomic signatures and cell type compositions in inflamed and non-inflamed colonic mucosa of ulcerative colitis 45 samples shares ulcerative, colonic, colitis
- GSE311760 IL-22 induces Paneth cell metaplasia in the colonic epithelium of ulcerative colitis, promoting wound healing via REG3A 18 samples shares ulcerative, colonic, colitis
- GSE298464 Single-cell RNA sequencing reveals ulcerative colitis patients’ response to anti-TNF-α therapy 16 samples shares ulcerative, colitis
- GSE266852 Comparison of differential gene expression in blood PBMCs from healthy controls, patients with rheumatoid arthritis,and patients with lupus using single-cell transcriptome sequencing analysis. 10 samples shares controls, healthy
- GSE158592 RNAseq analysis of blood from influenza infected patients and healthy controls SIG-2018 74 samples shares controls, healthy
- GSE196350 RNAseq analysis of blood from influenza infected patients and healthy controls 69 samples shares controls, healthy
- GSE302306 Transcriptomic Profiling of CD66b+ Neutrophils from Healthy Controls and Cardiac Surgery Patients with Vasoplegic and Septic Shock Syndromes Across Multiple Timepoints 68 samples shares controls, healthy
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.