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Effects of Trem2 depletion on gene expressions in a mouse photothrombotic stroke model

GSE280846 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2024/12/29 Platform GPL23479
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: 18 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.
Summary (written by the submitters)
Ischemic stroke is a major threat to public health. Microglia-mediated neuroinflammation is a double-edged sword for neuronal survival after stroke. Triggering receptor expressed on myeloid cells 2 (Trem2) is specifically expressed on the surface of myeloid cell, including microglia. Here, we applied a photothrombotic mouse model of stroke to better understand the role of Trem2 in post-stroke neuroinflammation.
Read the full summary ↓
In this model, Trem2 was sufficiently induced with sustainably elevated inflammatory responses. Our results demonstrated that Trem2-depletion can ameliorate ischemic injury with enhanced neuronal survival, reduced pro-inflammatory cytokine levels, and improved neurological functions. Our results suggested that Trem2 depletion is neuroprotective during ischemic stroke.
This dataset
Open GSE280846 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 GSE280846_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 PRJNA1180902 and SRA study SRP542582. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 9 samples read as cases, 9 as controls.

How we read this: Read from 18 sample titles: 18 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
Datasets on a similar topic

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