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MAIT cells in experimental autoimmune encephalomyelitis (EAE)

GSE234291 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/09/30 Platform GPL21103
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: 4 × EAE_CNS vs 4 × EAE_spleen vs 4 × Healthy_spleenGroups 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
Protective effect of TCR-mediated MAIT cell activation during experimental autoimmune encephalomyelitisNature communications · 2024
Summary (written by the submitters)
Multiple sclerosis (MS) is the most common inflammatory disease of the central nervous system (CNS) most likely caused by autoreactive T cells. Mucosal-associated invariant T (MAIT) cells are characterized by a semi-invariant T cell receptor (TCR) with which they recognize 5-(2-oxopropylideneamino)-6-D-ribitylaminouracil (5-OP-RU), a metabolite of the riboflavin (vitamin B2) pathway only present in yeast and bacteria.
Read the full summary ↓
MAIT cells have been detected in inflamed brain lesions of MS patients. However, functional analyses of CNS-infiltrating MAIT cells are lacking and require a characterisation in the MS animal model experimental autoimmune encephalomyelitis (EAE).
Published in
Protective effect of TCR-mediated MAIT cell activation during experimental autoimmune encephalomyelitis
Walkenhorst M, Sonner JK, Meurs N et al. · Nature communications 2024 · PMID 39468055 · doi:10.1038/s41467-024-53657-9
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 GSE234291_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 PRJNA980696 and SRA study SRP441393. Searching any of these in the dataset finder brings you back here.

Study design
4 × EAE_CNS vs 4 × EAE_spleen vs 4 × Healthy_spleen

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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.

Samples in this study
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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.