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RIPK1 protects naïve and regulatory T cells from TNFR1-induced apoptosis

GSE260973 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/06/20 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples
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
RIPK1 protects naive and regulatory T cells from TNFR1-induced apoptosisCell death and differentiation · 2024
Summary (written by the submitters)
The T cell population size is stringently controlled before, during, and after immune responses, as improper cell death regulation can result in autoimmunity and immunodeficiency. RIPK1 is an important regulator of peripheral T cell survival and homeostasis. However, whether different peripheral T cell subsets show a differential requirement for RIPK1 and which programmed cell death pathway they engage in vivo remains unclear. In this study, we used mesenteric lymph node (mLN) cells of Ripk1 KO mice, Ripk1/Casp8 double KO mice and their respective wild types to investigate this.
Published in
RIPK1 protects naive and regulatory T cells from TNFR1-induced apoptosis
Huysentruyt J, Steels W, Ruiz Perez M et al. · Cell death and differentiation 2024 · PMID 38734851 · doi:10.1038/s41418-024-01301-w
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE260973_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA1084758 and SRA study SRP493637. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 12 more — browse all 12 samples with per-sample file links →

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