Distinct activation programs in naïve and memory CD8 T cells govern progeny stemness and effector persistence
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 37 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
- 37 samples: 37 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 GSE342096_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 PRJNA1505581 and SRA study SRP720318. 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 37 sample titles: 37 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.
- GSM9896953 Sample1_Naive_Clone2
- GSM9896954 Sample2_AIMT_Clone2
- GSM9896955 Sample3_Memory_Clone2
- GSM9896956 Sample4_Naive_Clone2
- GSM9896957 Sample5_AIMT_Clone2
- GSM9896958 Sample6_Memory_Clone2
- GSM9896959 Sample7_Naive_Clone12
- GSM9896960 Sample8_AIMT_Clone12
- GSM9896961 Sample9_Memory_Clone12
- GSM9896962 Sample10_Naive_Clone12
- GSM9896963 Sample11_AIMT_Clone12
- GSM9896964 Sample13_AIMT_Clone12
- GSM9896965 Sample14_Naive_Clone2
- GSM9896966 Sample15_AIMT_Clone2
- GSM9896967 Sample16_Memory_Clone2
- GSM9899908 exp07_memory_NupHox_LmOVA_D3_D5_GEX_Data
- GSM9899909 exp07_memory_NupHox_LmOVA_D3_D5_Hashtag_Data
- GSM9901517 exp09_memory_NupHox_LCMV_OVA_D3_D5_GEX_Data
- GSM9901518 exp09_memory_NupHox_LCMV_OVA_D3_D5_Hashtag_Data
- GSM9903297 exp12_W1_OTI_LmOVA_W12_GEX_Data
- GSM9903298 exp12_W1_OTI_LmOVA_W12_Hashtag_Data
- GSM9903299 exp12_W2_OTI_LmOVA_W12_GEX_Data
- GSM9903300 exp12_W2_OTI_LmOVA_W12_Hashtag_Data
- GSM9903301 exp20_OTI_LmOVA_D6_GEX_Data
- GSM9903302 exp20_OTI_LmOVA_D6_Hashtag_Data
- GSM9905935 exp34_W1_memory_mixed_GEX_Data
- GSM9905936 exp34_W1_memory_mixed_Hashtag_Data
- GSM9905937 exp34_W2_memory_mixed_GEX_Data
- GSM9905938 exp34_W2_memory_mixed_Hashtag_Data
- GSM9905939 exp34_W3_memory_mixed_GEX_Data
- GSM9905940 exp34_W3_memory_mixed_Hashtag_Data
- GSM9905941 exp22_W2_multiome_GEX_Data
- GSM9905942 exp22_W2_multiome_Hashtags_Data
- GSM9905943 exp22_W2_multiome_ATAC_Data
- GSM9905944 exp22_W3_multiome_GEX_Data
- GSM9905945 exp22_W3_multiome_Hashtags_Data
- GSM9905946 exp22_W3_multiome_ATAC_Data
- GSE302682 Sleeping Beauty mutagenesis identifies BACH2 and other regulators promoting CD8+ T cell persistence and effector function under tumor-associated chronic antigen stimulation - RNAseq 66 samples shares cd8, persistence, effector
- GSE342312 T-bet and Runx3 orchestrate effector CD8 T cell differentiation and lineage fidelity through cooperative and distinct chromatin regulatory mechanisms [Multi-omics] 40 samples shares cd8, distinct, effector
- GSE270717 The m6A demethylase FTO controls activation-induced cell death in effector CD8+ T cells by modulating Fas expression 10 samples shares cd8, activation, effector
- GSE255887 HDAC1 controls the generation and maintenance of effector-like CD8+ T cells during chronic viral infection 76 samples shares cd8, effector
- GSE261250 Gfi1 controls the formation of effector CD8+ T cells during chronic infection and cancer 47 samples shares cd8, effector
- GSE274865 Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapy [CUT&Tag] 36 samples shares cd8, stemness
- GSE306744 Pre-division TCF1 downregulation determines long-term effector and memory CD8 T cell fates [RNA-Seq] 31 samples shares cd8, effector
- GSE157232 The CD8+ T cell tolerance checkpoint triggers a transcriptionally and epigenetically distinct differentiation state defined by protein translation defects 30 samples shares cd8, distinct
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.