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Brain and blood single-cell transcriptomic analysis in acute and subacute phases after experimental stroke

GSE225948 Mus musculus (mouse) Single-cell RNA-seq 29 samples Submitted 2023/06/14 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 29 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
29 samples: 29 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)
The secondary immune response to ischemic stroke progresses for days to weeks and involves glial and brain endothelium activation, recruitment of peripheral immune cells, and release of cytokines and chemokines. Whereas there is evidence that the acute inflammatory response contributes to the progression of ischemic brain injury, on the other hand, recent research points at a more multifaceted role of immune cells in brain ischemia, where immune cells participate in repair processes during the sub-acute and chronic stages.
Read the full summary ↓
Here we used single-cell sequencing to gain deeper insights into the impact of ischemic stroke on signature and the heterogeneity of brain immune cells, endothelial cells and circulating leukocytes in mice.
This dataset
Open GSE225948 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 GSE225948_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 PRJNA938082 and SRA study SRP424227. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38177281) ↗
Study design
29 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 29 sample titles: 29 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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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.