Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis.
RNA-seq (gene expression) · human · 117 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
- 117 samples: 95 distinct titles, 12 of them repeatedGroups 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
- Tracking in situ checkpoint inhibitor-bound target T cells in patients with checkpoint-induced colitisCancer cell · 2024
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 GSE189185_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 PRJNA781901 and SRA study SRP346600. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 117 sample titles: 95 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.
- GSM5693635 Pool 1: Sorted CD3_GEX_Tissue_Pool1
- GSM5693636 Pool 4: Sorted CD3_GEX_Tissue_Pool4
- GSM5693637 Pool 7: Sorted CD3_GEX_Blood_Pool7
- GSM5693638 Pool 10: Sorted CD3_GEX_Blood_Pool10_Repeat 1
- GSM5693639 Pool 13: Sorted CD3_GEX_Blood_Pool10_Repeat 2
- GSM5693640 Pool 16: Sorted CD3_GEX_Tissue_Pool16
- GSM5693641 Pool 19: Sorted CD3_GEX_Blood_Pool19_Repeat 1
- GSM5693642 Pool 22: Sorted CD3_GEX_Blood_Pool19_Repeat 2
- GSM5693643 Pool 1 Antibody: Sorted CD3_ADT_Tissue_Pool1
- GSM5693644 Pool 4 Antibody: Sorted CD3_ADT_Tissue_Pool4
- GSM5693645 Pool 7 Antibody: Sorted CD3_ADT_Blood_Pool7
- GSM5693646 Pool 10 Antibody: Sorted CD3_ADT_Blood_Pool10_Repeat 1
- GSM5693647 Pool 13 Antibody: Sorted CD3_ADT_Blood_Pool10_Repeat 2
- GSM5693648 Pool 16 Antibody: Sorted CD3_ADT_Tissue_Pool16
- GSM5693649 Pool 19 Antibody: Sorted CD3_ADT_Blood_Pool19_Repeat 1
- GSM5693650 Pool 22 Antibody: Sorted CD3_ADT_Blood_Pool19_Repeat 2
- GSM5693651 Pool 1 TCR: Sorted CD3_TCR_Tissue_Pool1
- GSM5693652 Pool 4 TCR: Sorted CD3_TCR_Tissue_Pool4
- GSM5693653 Pool 7 TCR: Sorted CD3_TCR_Blood_Pool7
- GSM5693654 Pool 10 TCR: Sorted CD3_TCR_Blood_Pool10_Repeat 1
- GSM5693655 Pool 13 TCR: Sorted CD3_TCR_Blood_Pool10_Repeat 2
- GSM5693656 Pool 16 TCR: Sorted CD3_TCR_Tissue_Pool16
- GSM5693657 Pool 19 TCR: Sorted CD3_TCR_Blood_Pool19_Repeat 1
- GSM5693658 Pool 22 TCR: Sorted CD3_TCR_Blood_Pool19_Repeat 2
- GSM5695828 GI Biobank Corona Recovery 17 (GI 6266)
- GSM5695829 GI Biobank Corona Recovery 15 (GI 6264)
- GSM5695830 PRISE 31
- GSM5695831 PRISE 14
- GSM5695832 GI 6275
- GSM5695833 PRISE 23
- GSM5695834 GI 6967_B8
- GSM5695835 GI 6967_B9
- GSM5695836 GI 6278
- GSM5695837 GI 6925
- GSM5695838 GI 6658
- GSM5695839 GI 4980
- GSM5695840 BB4652
- GSM5695841 GI 6274
- GSM5695842 GI 3667 (#1)
- GSM5695843 TIP 517
+ 77 more — browse all 117 samples with per-sample file links →
- GSE189040 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - CD3 scRNA-Seq 24 samples shares microdomains, ulcerative, checkpoint, divergent, spatial, therapy, colitis, repair
- GSE189184 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - Spatial Transcriptomics 16 samples shares microdomains, ulcerative, checkpoint, divergent, spatial, therapy, colitis, repair
- GSE190564 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - whole tissue scRNA-Seq 62 samples shares microdomains, ulcerative, checkpoint, divergent, spatial, therapy, colitis, repair
- GSE189754 Divergent spatial microdomains drive inflammation and repair in Ulcerative and Immune Checkpoint Therapy Colitis - CD45 scRNA-Seq 15 samples shares microdomains, ulcerative, checkpoint, divergent, spatial, therapy, colitis, repair
- GSE298464 Single-cell RNA sequencing reveals ulcerative colitis patients’ response to anti-TNF-α therapy 16 samples shares ulcerative, therapy, colitis
- GSE228597 Immunologic drivers of immune checkpoint inhibitor therapy myocarditis, fatality and anti-tumor response in cancer patients 75 samples shares checkpoint, therapy
- GSE318641 Dynamic interaction between tentacle-tethered microdomains in Integrator and NELF regulates the promoter-proximal pause checkpoint 61 samples shares microdomains, checkpoint
- GSE278119 Clonally expanded effector CD4+ cytotoxic T lymphocytes are associated with severe neurological adverse events after immune checkpoint inhibitor therapy 44 samples shares checkpoint, therapy
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.