Single-cell multiomic analysis identifies macrophage subpopulations in promoting cardiac repair
Single-cell RNA-seq · mouse · 48 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
- 48 samples: 21 conditions, mostly in duplicateGroups 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
- Single-cell multiomic analysis identifies macrophage subpopulations in promoting cardiac repairThe Journal of clinical investigation · 2024
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 GSE225615_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 PRJNA936797 and SRA study SRP423452. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 42 samples.
How we read this: 21 replicated groups read from 48 sample titles; they account for 42 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.
- GSM7051160 P1_MI_3D_IZ_rep1
- GSM7051161 P1_MI_3D_BZ_rep1
- GSM7051162 P1_MI_3D_RZ_rep1
- GSM7051163 P1_Sham_3D_IZ_rep1
- GSM7051164 P1_Sham_3D_BZ_rep1
- GSM7051165 P1_Sham_3D_RZ_rep1
- GSM7051166 P1_MI_7D_IZ_rep1 P1_MI_7D_IZ
- GSM7051167 P1_MI_7D_IZ_rep2 P1_MI_7D_IZ
- GSM7051168 P1_MI_7D_BZ_rep1 P1_MI_7D_BZ
- GSM7051169 P1_MI_7D_BZ_rep2 P1_MI_7D_BZ
- GSM7051170 P1_MI_7D_RZ_rep1 P1_MI_7D_RZ
- GSM7051171 P1_MI_7D_RZ_rep2 P1_MI_7D_RZ
- GSM7051172 P1_Sham_7D_IZ_rep1 P1_Sham_7D_IZ
- GSM7051173 P1_Sham_7D_IZ_rep2 P1_Sham_7D_IZ
- GSM7051174 P1_Sham_7D_BZ_rep1 P1_Sham_7D_BZ
- GSM7051175 P1_Sham_7D_BZ_rep2 P1_Sham_7D_BZ
- GSM7051176 P1_Sham_7D_RZ_rep1 P1_Sham_7D_RZ
- GSM7051177 P1_Sham_7D_RZ_rep2 P1_Sham_7D_RZ
- GSM7051178 P10_MI_3D_IZ_rep2 P10_MI_3D_IZ
- GSM7051179 P10_MI_3D_IZ_rep3 P10_MI_3D_IZ
- GSM7051180 P10_MI_3D_BZ_rep2 P10_MI_3D_BZ
- GSM7051181 P10_MI_3D_BZ_rep3 P10_MI_3D_BZ
- GSM7051182 P10_MI_3D_RZ_rep2 P10_MI_3D_RZ
- GSM7051183 P10_MI_3D_RZ_rep3 P10_MI_3D_RZ
- GSM7051184 P10_Sham_3D_IZ_rep2 P10_Sham_3D_IZ
- GSM7051185 P10_Sham_3D_IZ_rep3 P10_Sham_3D_IZ
- GSM7051186 P10_Sham_3D_BZ_rep2 P10_Sham_3D_BZ
- GSM7051187 P10_Sham_3D_BZ_rep3 P10_Sham_3D_BZ
- GSM7051188 P10_Sham_3D_RZ_rep2 P10_Sham_3D_RZ
- GSM7051189 P10_Sham_3D_RZ_rep3 P10_Sham_3D_RZ
- GSM7051190 P10_MI_7D_IZ_rep1 P10_MI_7D_IZ
- GSM7051191 P10_MI_7D_IZ_rep2 P10_MI_7D_IZ
- GSM7051192 P10_MI_7D_BZ_rep1 P10_MI_7D_BZ
- GSM7051193 P10_MI_7D_BZ_rep2 P10_MI_7D_BZ
- GSM7051194 P10_MI_7D_RZ_rep1 P10_MI_7D_RZ
- GSM7051195 P10_MI_7D_RZ_rep2 P10_MI_7D_RZ
- GSM7051196 P10_Sham_7D_IZ_rep1 P10_Sham_7D_IZ
- GSM7051197 P10_Sham_7D_IZ_rep2 P10_Sham_7D_IZ
- GSM7051198 P10_Sham_7D_BZ_rep1 P10_Sham_7D_BZ
- GSM7051199 P10_Sham_7D_BZ_rep2 P10_Sham_7D_BZ
+ 8 more — browse all 48 samples with per-sample file links →
- GSE306718 Macrophage Cluster of Differentiation 163 promotes post-infarction cardiac repair and preserves left ventricular function via osteopontin 37 samples shares macrophage, cardiac, repair
- GSE215963 Subclonal evolution revealed by single-cell profiles of expressed mutations identifies adaptation mechanisms to immunotherapy in melanoma. 1497 samples shares single-cell, identifies
- GSE280514 Spatially-restricted and ontogenically-distinct hepatic macrophages are required for tissue repair. 48 samples shares macrophage, repair
- GSE263895 Both host and parasite non-coding RNAs co-ordinate the regulation of macrophage gene expression to reduce pro-inflammatory immune responses and promote tissue repair pathways during infection with fasciola hepatica 40 samples shares macrophage, repair
- GSE269748 A single-cell atlas deconstructs heterogeneity across multiple models in murine traumatic brain injury and identifies novel cell-specific targets 36 samples shares single-cell, identifies
- GSE220691 Kidney Single-Cell Atlas Reveals Macrophage Heterogeneity in Progression and Regression of Cisplatin Induced AKI. 22 samples shares single-cell, macrophage
- GSE314943 Single-cell multiomics uncovers an endothelial mechanosensitive PIEZO1-IL-33 axis driving pulmonary fibrosis 18 samples shares single-cell, multiomic
- GSE297298 Single-cell RNA-sequencing identifies anti-cancer immune phenotypes in the early lung metastatic niche during breast cancer 18 samples shares single-cell, identifies
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.