ATAC-seq profiling of lineage-traced exhausted and memory-like CD8+ T cell subsets during tumor progression
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 24 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
- Mus musculus (mouse)
- Samples
- 24 samples: 24 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.
Read the full summary ↓
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 GSE337898_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 PRJNA1491467 and SRA study SRP716101. 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 24 sample titles: 24 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.
- GSM9862442 DLN DN CD8+ T cells ATAC-seq (replicate 1)
- GSM9862443 DLN DN CD8+ T cells ATAC-seq (replicate 2)
- GSM9862444 DLN LAG3-tdTomato+ CD8+ T cells ATAC-seq
- GSM9862445 DLN tdTomato+ CD8+ T cells ATAC-seq (replicate 1)
- GSM9862446 DLN tdTomato+ CD8+ T cells ATAC-seq (replicate 2)
- GSM9862447 NDLN DN CD8+ T cells ATAC-seq (replicate 1)
- GSM9862448 NDLN DN CD8+ T cells ATAC-seq (replicate 2)
- GSM9862449 NDLN LAG3-tdTomato+ CD8+ T cells ATAC-seq
- GSM9862450 NDLN tdTomato+ CD8+ T cells ATAC-seq (replicate 1)
- GSM9862451 NDLN tdTomato+ CD8+ T cells ATAC-seq (replicate 2)
- GSM9862452 Tumor DN CD8+ T cells ATAC-seq (replicate 1)
- GSM9862453 Tumor DN CD8+ T cells ATAC-seq (replicate 2)
- GSM9862454 Tumor DN CD8+ T cells ATAC-seq (replicate 3)
- GSM9862455 Tumor DN CD8+ T cells ATAC-seq (replicate 4)
- GSM9862456 Tumor LAG3+tdTomato+ CD8+ T cells ATAC-seq (replicate 1)
- GSM9862457 Tumor LAG3+tdTomato+ CD8+ T cells ATAC-seq (replicate 2)
- GSM9862458 Tumor LAG3+tdTomato+ CD8+ T cells ATAC-seq (replicate 3)
- GSM9862459 Tumor LAG3+tdTomato+ CD8+ T cells ATAC-seq (replicate 4)
- GSM9862460 Tumor LAG3-tdTomato+ CD8+ T cells ATAC-seq (replicate 1)
- GSM9862461 Tumor LAG3-tdTomato+ CD8+ T cells ATAC-seq (replicate 2)
- GSM9862462 Tumor LAG3-tdTomato+ CD8+ T cells ATAC-seq (replicate 3)
- GSM9862463 Tumor tdTomato+ CD8+ T cells ATAC-seq (replicate 1)
- GSM9862464 Tumor tdTomato+ CD8+ T cells ATAC-seq (replicate 2)
- GSM9862465 Tumor tdTomato+ CD8+ T cells ATAC-seq (replicate 3)
- GSE262842 Antitumor progenitor exhausted CD8 T cells are sustained with TCR engagement [ATACseq] 24 samples shares cd8, exhausted
- GSE235005 Nutrient-driven histone code determines exhausted CD8+ T cell fates [ChIP-seq] 50 samples shares cd8, exhausted
- GSE271884 GFI1-driven transcriptional and epigenetic programs maintain memory CD8+ T cell persistence [ATAC-seq]. 30 samples shares cd8, atac-seq
- GSE281498 The transcription factor BATF pioneers the differentiation program of cytolytic effector CD8+ T cells through the direct interaction with IRF4 (ATAC-seq) 20 samples shares cd8, atac-seq
- GSE285187 A core stemness program in exhausted CD8+ T cells 24 samples shares cd8, exhausted
- GSE252358 Acetylcyssteine synergizes PD-1 blockers against colorectal cancer progression by promoting TCF1+PD1+CD8+ T cell differentiation in mice 10 samples shares cd8, progression
- GSE263359 Chromatin Modification Abnormalities by CHD7 and KMT2C Loss Promote Medulloblastoma Progression [ATAC-seq] 11 samples shares progression, atac-seq
- GSE304763 A pan-immunotherapy signature to predict intratumoral CD8+ T cell expansions [scTCR_immunotherapies] 91 samples shares cd8
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.