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Single cell transcriptomic analyses of the dynamic local and systemic response to cardiac injury in mice and zebrafish [mouse]

GSE227189 Mus musculus (mouse) Single-cell RNA-seq 28 samples Submitted 2024/11/07 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 28 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
28 samples: 28 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.
Paper
Cross-species single-cell RNA-seq analysis reveals disparate and conserved cardiac and extracardiac inflammatory responses upon heart injuryCommunications biology · 2024
Summary (written by the submitters)
Mice respond to myocardial infarction (MI) by generating a fibrotic scar in the heart. This is accompanied by systemic inflammation after the MI resolves. In contrast, zebrafish can fully regenerate their heart after heart injury. To further investigate the divergent species’ responses to cardiac injury, single cell transcriptomic analyses were performed on the heart, blood, liver, kidney, and pancreatic islets.
Published in
Cross-species single-cell RNA-seq analysis reveals disparate and conserved cardiac and extracardiac inflammatory responses upon heart injury
Cortada E, Yao J, Xia Y et al. · Communications biology 2024 · PMID 39627536 · doi:10.1038/s42003-024-07315-x
This dataset
Open GSE227189 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 GSE227189_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 PRJNA943552 and SRA study SRP426910. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39627536) ↗
Study design
28 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 28 sample titles: 28 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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