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Whole lung gene expression in Tcrd-/- mice after Burkholderia thailandensis infection

GSE254868 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/06/28 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 16 samples, each with a distinct title — no replicated groupsGroups 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
γδ T Cells Mediate Protection against Neutrophil-associated Lung Inflammation in Pulmonary MelioidosisAmerican journal of respiratory cell and molecular biology · 2024
Summary (written by the submitters)
Neutrophil recruitment appears critical to the pulmonary defense to B. pseudomallei. Therefore, we hypothesized that γδ T cells are critical regulators of pulmonary bacterial clearance given their proposed regulation of neutrophil recruitment to the lung. To investigate this hypothesis, we leveraged multiple in vivo models of pulmonary melioidosis to further understand the mechanisms by which γδ T cells regulate inflammation early in severe pulmonary infection.
Read the full summary ↓
Included in this investigation, we assessed whole lung bulk RNA-sequencing data in mice with and without γδ T cells after infection with Burkholderia thailandensis.
Published in
γδ T Cells Mediate Protection against Neutrophil-associated Lung Inflammation in Pulmonary Melioidosis
Wright SW, Sengyee S, Ekchariyawat P et al. · American journal of respiratory cell and molecular biology 2024 · PMID 38935886 · doi:10.1165/rcmb.2024-0072OC
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 GSE254868_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 PRJNA1072113 and SRA study SRP487535. Searching any of these in the dataset finder brings you back here.

Study design
16 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 16 sample titles: 16 distinct titles with little repetition. 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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