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Transcriptome of human peripheral blood regulatory T cells with distinct ex vivo expansion profile

GSE208111 Homo sapiens (human) RNA-seq (gene expression) 19 samples Submitted 2024/04/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 19 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
Homo sapiens (human)
Samples
19 samples: 8 × ARTEMIS # vs 6 × Post-KTx # vs 3 × T1D # vs 2 × Pre-KTx #Groups 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
Selective decrease of donor-reactive T(regs) after liver transplantation limits T(reg) therapy for promoting allograft tolerance in humansScience translational medicine · 2022
Summary (written by the submitters)
The UCSF Treg cell therapy program manufactured over 60 human regulatory T cell (Treg) products under the GMP condition in support of 9 clinical trials between 2011 and 2021. These products were manufactured using two alternative protocols of either two rounds of polyclonal stimulations (PolyTregs) or first allogeneic B cell stimulation followed by polyclonal stimulation (arTregs).
Read the full summary ↓
A high degree of individual variability in Treg expansion with both protocols was observed. RNA-seq analysis was performed on freshly isolated peripheral blood Tregs to identify transcriptome profile associated with Treg expansions.
Published in
Selective decrease of donor-reactive T(regs) after liver transplantation limits T(reg) therapy for promoting allograft tolerance in humans
Tang Q, Leung J, Peng Y et al. · Science translational medicine 2022 · PMID 36322627 · doi:10.1126/scitranslmed.abo2628
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 GSE208111_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 PRJNA858412 and SRA study SRP386240. Searching any of these in the dataset finder brings you back here.

Study design
8 × ARTEMIS # vs 6 × Post-KTx # vs 3 × T1D # vs 2 × Pre-KTx #

Supports a between-group comparison across 19 samples.

How we read this: 4 replicated groups read from 19 sample titles; they account for 19 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.