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Transcriptome profiles of wild-type, IRF8KO microglia

GSE266422 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/07/01 Platform GPL19057
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: 3 × WT_P9 vs 3 × IRF8KO_P9 vs 3 × WT_P14 vs 3 × IRF8KO_P14Groups 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
IRF8 defines the epigenetic landscape in postnatal microglia, thereby directing their transcriptome programsNature immunology · 2024
Summary (written by the submitters)
The lineage-determining transcription factor IRF8's function in microglia is unclear. Our study aims to shed light on this by analyzing the genome-wide, temporal transcriptome profiles of wild-type and IRF8KO microglia. We used deep-sequencing and differential analysis to identify the effects of IRF8 on transcription programs in microglia, such as microglia identity gene expression. This study provides a new understanding of the transcriptional programs in microglia.
Published in
IRF8 defines the epigenetic landscape in postnatal microglia, thereby directing their transcriptome programs
Saeki K, Pan R, Lee E et al. · Nature immunology 2024 · PMID 39313544 · doi:10.1038/s41590-024-01962-2
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 GSE266422_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 PRJNA1107154 and SRA study SRP505336. Searching any of these in the dataset finder brings you back here.

Study design
3 × WT_P9 vs 3 × IRF8KO_P9 vs 3 × WT_P14 vs 3 × IRF8KO_P14

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 12 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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