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Alzheimer’s disease-induced phagocytic microglia express a specific profile of coding and non-coding RNAs [lncRNA]

GSE229418 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2024/03/20 Platform GPL21493
At a glance

Single-cell RNA-seq · mouse · 16 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
16 samples: 7 × WT microglia (Me-X04 neg) vs 5 × TG microglia (Me-X04 neg) vs 4 × TG microglia (Me-X04 pos)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
Alzheimer's disease-induced phagocytic microglia express a specific profile of coding and non-coding RNAsAlzheimer's & dementia : the journal of the Alzheimer's Association · 2024
Summary (written by the submitters)
To detect total RNA in microglia derived from AD mice (5xFAD) brain we single cell sorted Cd11b+ and Cd45+ cells divided by Methoxy-X04 staining (Ab aggregates) positivity We performed differentially expression analysis of RNA-seq of wild-type microglia (Me-X04 neg), non-phagocytic AD microglia (Me-X04 neg), phagocytic AD microglia (Me-X04 positive)
Published in
Alzheimer's disease-induced phagocytic microglia express a specific profile of coding and non-coding RNAs
Scoyni F, Giudice L, Väänänen MA et al. · Alzheimer's & dementia : the journal of the Alzheimer's Association 2024 · PMID 37828821 · doi:10.1002/alz.13502
This dataset
Open GSE229418 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 GSE229418_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 PRJNA954393 and SRA study SRP432040. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37828821) ↗
Study design
7 × WT microglia (Me-X04 neg) vs 5 × TG microglia (Me-X04 neg) vs 4 × TG microglia (Me-X04 pos)

Supports a between-group comparison across 16 samples.

How we read this: 3 replicated groups read from 16 sample titles; they account for 16 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

Search all mouse RNA-seq datasets in GEO →

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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.