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Neonatal inflammation impairs developmentally-associated subsets of microglia and promotes highly reactive microglia subset

GSE165113 Mus musculus (mouse) Single-cell RNA-seq 38 samples Submitted 2024/12/31 Platform GPL19057Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 38 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
38 samples: 12 conditions, mostly in triplicateGroups 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
Neonatal inflammation impairs developmentally-associated microglia and promotes a highly reactive microglial subsetBrain, behavior, and immunity · 2025
Summary (written by the submitters)
Single-cells inDrops RNAseq analyses of neonatal neuroinflammation mice models comprising 20 samples with technical and biological replicates
Published in
Neonatal inflammation impairs developmentally-associated microglia and promotes a highly reactive microglial subset
Dufour A, Heydari Olya A, Foulon S et al. · Brain, behavior, and immunity 2025 · PMID 39322088 · doi:10.1016/j.bbi.2024.09.019
This dataset
Open GSE165113 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 GSE165113_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA693280 and SRA study SRP302389. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39322088) ↗
Study design
12 conditions, mostly in triplicate
P5-IL1B ×6 P5-PBS ×6 P1 IL1 ×3 P3 IL1 ×3 P5 IL1 ×3 P1 PBS ×3 P3 PBS ×3 P5 PBS ×3 +4 more

Supports a between-group comparison across 38 samples.

How we read this: 12 replicated groups read from 38 sample titles; they account for 38 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
Datasets on a similar topic

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