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An essential role for the IL-2 receptor in Treg cell function

GSE84553 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2016/08/29 Platform GPL17021
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.
Summary (written by the submitters)
Regulatory T (Treg) cells, expressing abundant amounts of the IL-2 receptor (IL-2R), are reliant on IL-2 produced by activated T cells. This feature implied a key role for a simple network based on IL-2 consumption by Treg cells in their suppressor function. However, congenital deficiency in IL-2R results in reduced expression of the Treg lineage specification factor Foxp3, confounding experimental efforts to understand the role of IL-2R expression and signaling in Treg suppressor function.
Read the full summary ↓
Using genetic gain and loss of function approaches, we demonstrate that IL-2 capture is dispensable for control of CD4+ T cells, but is important for limiting CD8+ T cell activation, and that IL-2R dependent STAT5 transcription factor activation plays an essential role in Treg suppressor function separable from T cell receptor signaling.
This dataset
Open GSE84553 in finder → Find more mouse RNA-seq datasets →
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.

Series matrix ↓
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 GSE84553_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA329604 and SRA study SRP078918. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27595233) ↗
Study design
A cohort of 12 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run TC_YB_1 … TC_YB_12 and carry no group information.

Samples in this study
Datasets on a similar topic

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