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Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice

GSE264105 Mus musculus (mouse) Single-cell RNA-seq 1111 samples Submitted 2024/10/15 Platform GPL21626
At a glance

Single-cell RNA-seq · mouse · 1111 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
1111 samples: 1111 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)
Microglia are highly responsive to their local environment and signals from the periphery. Blood plasma proteins readily permeate the healthy brain parenchyma. However, whether microglia are responsive to such proteins is unclear. Here, we identify a stable population of microglia takes up plasma proteins in a region-specific manner in healthy brains.
Read the full summary ↓
To understand these microglia at the single cell transcriptomic level and correlate their transcriptome with plasma uptake intensity, we sorted plasma-high, plasma-low, and plasma-negative microglia from young mice (3-month-old) and perform plate-based scRNA-seq.
This dataset
Open GSE264105 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 GSE264105_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 PRJNA1100999 and SRA study SRP502161. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
1111 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 the first 400 of 1111 sample titles: 400 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

+ 1071 more — browse all 1111 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.