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Analysis of different mouse P14 CD8+T cell subset gene signatures in presence and absence of Tim-3+ Treg during LCMV CL13 infection

GSE254211 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/07/03 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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
Tim-3 Is Required for Regulatory T Cell-Mediated Promotion of T Cell Exhaustion and Viral Persistence during Chronic Lymphocytic Choriomeningitis Virus InfectionJournal of immunology (Baltimore, Md. : 1950) · 2024
Summary (written by the submitters)
Treg-specific Tim-3 deletion alters the transcriptional profile of specific major WT P14 Tex subsets early during chronic infection.
Published in
Tim-3 Is Required for Regulatory T Cell-Mediated Promotion of T Cell Exhaustion and Viral Persistence during Chronic Lymphocytic Choriomeningitis Virus Infection
Nieves-Rosado HM, Banerjee H, Gocher-Demske A et al. · Journal of immunology (Baltimore, Md. : 1950) 2024 · PMID 39345172 · doi:10.4049/jimmunol.2400119
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 GSE254211_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 PRJNA1069017 and SRA study SRP485942. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
PD-1-Tim-3- P14 T cells isolated from Cre-onl… ×3 PD-1+Tim-3- P14 T cells isolated from Cre-onl… ×3 PD-1+Tim-3+ P14 T cells isolated from Cre-onl… ×3 PD-1-Tim-3- P14 T cells isolated from Treg-sp… ×3 PD-1+Tim-3- P14 T cells isolated from Treg-sp… ×3 PD-1+Tim-3+ P14 T cells isolated from Treg-sp… ×2 PD-1+Tim-3+ P14 T cells isolated from Treg-sp… ×1

Supports a between-group comparison across 17 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 17 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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