Opposing functions of distinct regulatory T cell subsets in colorectal cancer
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 142 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Topic
- Colorectal cancerThis series is part of our curated briefing on it.
- Samples
- 142 samples: 142 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
- Opposing functions of distinct regulatory T cell subsets in colorectal cancerImmunity · 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 GSE290623_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1229418 and SRA study SRP648608. 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 142 sample titles: 142 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.
- GSM8818233 patient2, T-cells, tumor, GEX
- GSM8818234 patient2, T-cells, tumor, ATAC
- GSM8818235 patient2, T-cells, nat, GEX
- GSM8818236 patient2, T-cells, nat, ATAC
- GSM8818237 patient4, T-cells, tumor, GEX
- GSM8818238 patient4, T-cells, tumor, ATAC
- GSM8818239 patient4, T-cells, nat, GEX
- GSM8818240 patient4, T-cells, nat, ATAC
- GSM8818241 patient7, T-cells, tumor, GEX
- GSM8818242 patient7, T-cells, tumor, ATAC
- GSM8818243 patient7, T-cells, nat, GEX
- GSM8818244 patient7, T-cells, nat, ATAC
- GSM8818245 T-cells, gut, GEX
- GSM8818246 T-cells, gut, TCR
- GSM8818247 T-cells, gut, HTO
- GSM8818248 T-cells, tumor, GEX
- GSM8818249 T-cells, tumor, TCR
- GSM8818250 T-cells, tumor, HTO
- GSM8818251 nonT-cells, gut, GEX
- GSM8818252 nonT-cells, gut, HTO
- GSM8818253 nonT-cells, tumor, GEX
- GSM8818254 nonT-cells, tumor, HTO
- GSM8818255 Multiome, T-cells, gut, GEX
- GSM8818256 Multiome, T-cells, gut, ATAC
- GSM8818257 Multiome, T-cells, tumor, GEX
- GSM8818258 Multiome, T-cells, tumor, ATAC
- GSM8818259 T-cells, gut, GEX [mm10_tcr_2_4_6_weeks]
- GSM8818260 T-cells, gut, TCR [mm10_tcr_2_4_6_weeks]
- GSM8818261 T-cells, gut, HTO [mm10_tcr_2_4_6_weeks]
- GSM8818262 T-cells, lymph node, GEX [mm10_tcr_2_4_6_weeks]
- GSM8818263 T-cells, lymph node, TCR [mm10_tcr_2_4_6_weeks]
- GSM8818264 T-cells, lymph node, HTO [mm10_tcr_2_4_6_weeks]
- GSM8818265 T-cells, tumor, GEX [mm10_tcr_2_4_6_weeks]
- GSM8818266 T-cells, tumor, ADT [mm10_tcr_2_4_6_weeks]
- GSM8818267 T-cells, tumor, HTO [mm10_tcr_2_4_6_weeks]
- GSM8818326 JM209B,tumor
- GSM8818327 JM210B,tumor
- GSM8818328 JM212B,tumor
- GSM8818329 JM213B,tumor
- GSM8818330 JM214B,tumor
+ 102 more — browse all 142 samples with per-sample file links →
- GSE12032 Inherent gene signature of stage II and III colorectal cancer leads in individual recurrence 198 samples same disease briefing · shares colorectal
- GSE250000 Bulk RNA-sequencing of transduced colorectal cancer cell line HCT-116 and breast cancer cell line MCF-7 overexpressing full-lenght p53β or p53β-stop-lost. 4 samples same disease briefing · shares colorectal
- GSE110009 Single cell transcriptome landscape of primary and metastatic tumor in colon cancer 76 samples same disease briefing
- GSE109308 Single-cell transcriptomic survey of adenomatous polyposis patients with germline APC mutations 97 samples same disease briefing
- GSE97179 Single Cell Methylome Signatures Reveal Distinct Neuronal Populations and Regulatory Elements in the Mammalian Cortex 6172 samples shares regulatory, distinct
- GSE292300 A core transcriptional regulatory circuitry controls super-enhancer-driven activation of LGR5 in colorectal cancer: ChIP-seq 76 samples shares regulatory, colorectal
- GSE292302 A core transcriptional regulatory circuitry controls super-enhancer-driven activation of LGR5 in colorectal cancer: RNA-seq 42 samples shares regulatory, colorectal
- GSE266750 GATA6 is a Novel Regulator of Gene Expression and 3D Genome in Colorectal Cancer 75 samples shares colorectal
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.