Regulatory circuits of mitophagy restricts cell death for mounting memory CD8+ T cell formation
RNA-seq (gene expression) · mouse · 10 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
- Mus musculus (mouse)
- Samples
- 10 samples: 5 × Ctrl vs 5 × ParkinKOGroups 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
- Regulatory circuits of mitophagy restrict distinct modes of cell death during memory CD8(+) T cell formationScience immunology · 2023
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 GSE223004_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 PRJNA924691 and SRA study SRP417832. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 10 of them. 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.
- GSM6938179 Ctrl_1 Ctrl
- GSM6938180 Ctrl_2 Ctrl
- GSM6938181 Ctrl_3 Ctrl
- GSM6938182 Ctrl_4 Ctrl
- GSM6938183 Ctrl_5 Ctrl
- GSM6938184 ParkinKO_1 ParkinKO
- GSM6938185 ParkinKO_2 ParkinKO
- GSM6938186 ParkinKO_3 ParkinKO
- GSM6938187 ParkinKO_4 ParkinKO
- GSM6938188 ParkinKO_5 ParkinKO
- GSE215759 Mettl3-dependent m6A modification is essential for effector differentiation and memory formation of CD8+ T cells [RNA-seq] 15 samples shares cd8, formation, memory
- GSE306744 Pre-division TCF1 downregulation determines long-term effector and memory CD8 T cell fates [RNA-Seq] 31 samples shares cd8, memory
- GSE341988 Sequential pathogen exposure normalizes the brain neuroimmune microenvironment and reveals a tissue-resident memory CD8 T cell-microglia axis shaping adult neurogenesis 8 samples shares cd8, memory
- GSE261250 Gfi1 controls the formation of effector CD8+ T cells during chronic infection and cancer 47 samples shares cd8, formation
- 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, regulatory
- GSE342096 Distinct activation programs in naïve and memory CD8 T cells govern progeny stemness and effector persistence 37 samples shares cd8, memory
- GSE273195 H2A.Z regulates memory CD8+ T cell recall response [4] 34 samples shares cd8, memory
- GSE271884 GFI1-driven transcriptional and epigenetic programs maintain memory CD8+ T cell persistence [ATAC-seq]. 30 samples shares cd8, memory
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.