Spatiotemporal dynamics of the cardioimmune niche during lesion repair [scRNA-seq]
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
- Spatiotemporal dynamics of the cardioimmune niche during lesion repairNature cardiovascular research · 2025
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE280373_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA1178116 and SRA study SRP540997. Searching any of these in the dataset finder brings you back here.
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.
- GSM8595757 Cryoablation nonmyocytes Day1 batch 1 scRNA-seq GEX
- GSM8595758 Cryoablation nonmyocytes Day1 batch 1 scRNA-seq CMO
- GSM8595759 Cryoablation nonmyocytes Day1 batch2 scRNA-seq GEX
- GSM8595760 Cryoablation nonmyocytes Day1 batch2 scRNA-seq CMO
- GSM8595761 Cryoablation nonmyocytes Day3 scRNA-seq GEX
- GSM8595762 Cryoablation nonmyocytes Day3 scRNA-seq CMO
- GSM8595763 Cryoablation nonmyocytes Day7 scRNA-seq GEX
- GSM8595764 Cryoablation nonmyocytes Day7 scRNA-seq CMO
- GSM8595765 Cryoablation nonmyocytes Day28 scRNA-seq GEX
- GSM8595766 Cryoablation nonmyocytes Day28 scRNA-seq CMO
- GSM8595767 Cryoablation nonmyocytes Day56 scRNA-seq GEX
- GSM8595768 Cryoablation nonmyocytes Day56 scRNA-seq CMO
- GSM8595769 Cryoablation CM batch1 Day 1-56 snRNA-seq GEX
- GSM8595770 Cryoablation CM batch1 Day 1-56 snRNA-seq CMO
- GSM8595771 Cryoablation CM batch2 Day 1-56 snRNA-seq GEX
- GSM8595772 Cryoablation CM batch2 Day 1-56 snRNA-seq CMO
- GSM8595773 LAD + sham nonmyocytes Day1 scRNA-seq GEX
- GSM8595774 LAD + sham nonmyocytes Day1 scRNA-seq CMO
- GSM8595775 LAD + sham nonmyocytes Day3 scRNA-seq GEX
- GSM8595776 LAD + sham nonmyocytes Day3 scRNA-seq CMO
- GSM8595777 LAD + sham nonmyocytes Day7 scRNA-seq GEX
- GSM8595778 LAD + sham nonmyocytes Day7 scRNA-seq CMO
- GSM8595779 LAD + sham nonmyocytes Day28 scRNA-seq GEX
- GSM8595780 LAD + sham nonmyocytes Day28 scRNA-seq CMO
- GSM8595781 LAD + sham nonmyocytes Day56 scRNA-seq GEX
- GSM8595782 LAD + sham nonmyocytes Day56 scRNA-seq CMO
- GSM8595783 LAD + sham CM Day 1-56 snRNA-seq GEX
- GSM8595784 LAD + sham CM Day 1-56 snRNA-seq CMO
- GSE303460 Spatiotemporal single-cell atlas of suture stem cell dynamics in craniosynostosis [scRNA-Seq] 14 samples shares spatiotemporal, scrna-seq, dynamics
- GSE277228 Changing dynamics of the fibroblast differentiation hierarchy during mammary gland morphogenesis and tumorigenesis [scRNA-Seq I] 13 samples shares scrna-seq, dynamics
- GSE290194 Repair-Associated Macrophages Increase after Early-phase Microglia Attenuation to Promote Ischemic Stroke Recovery [scRNA-Seq] 16 samples shares scrna-seq, repair
- GSE287528 Gas6-Axl signaling drives oral regenerative wound repair [scRNA-seq] 10 samples shares scrna-seq, repair
- GSE248386 ILC2 regulate a Pi16+ fibroblast progenitor niche in the pancreas (acute pancreatitis scRNA-seq) 10 samples shares scrna-seq, niche
- GSE264105 Plate-based scRNA-seq of plasma-positive microglia and plasma-negative microglia in young mice 1111 samples shares scrna-seq
- GSE271100 Stem cells tightly regulate dead cell clearance to maintain tissue fitness [scRNA-seq] 1037 samples shares scrna-seq
- GSE277789 Spatiotemporal and genetic cell lineage tracing of endodermal organogenesis at single-cell resolution [Smart-seq3-RNA-seq-add] 830 samples shares spatiotemporal
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.