Human Keloid Skin Single-Cell Meta-Analysis Across Asian, Black and White Populations

Ziad Alkouz's meta-analysis integrates eight public single-cell RNA sequencing studies on human keloid skin. The dataset comprises 487,293 cells from 147 samples across 112 donors, processed using scVI/scANVI and analyzed for differential abundance and gene expression. It was last updated on 2026-05-18.

Use Cases

• Identify cell type abundance changes in keloid versus normal skin based on the integrated single-cell data.
• Analyze ethnicity-specific gene expression patterns linked to TGF-β/SMAD or YAP/TAZ signaling pathways.
• Benchmark computational pipelines for single-cell meta-analysis using the provided standardized processing workflow.
• Investigate endothelial and fibroblast expansion in keloid pathogenesis across diverse populations.

Strengths

• Integrates data from 112 donors and 487,293 cells, providing a substantial sample size for meta-analysis.
• Employs standardized computational pipelines (scVI/scANVI) and rigorous quality control for reproducibility.
• Explicitly analyzes data across Asian, Black, and White populations, enabling studies of ethnic disparities.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.
• The dataset is small in file size (13.3 KB), suggesting it contains summary results rather than raw single-cell data.

Provenance

Source

figshare

Collection Method

Meta-analysis of eight publicly available human skin single-cell RNA sequencing datasets.

Freshness

Last updated 2026-05-18 09:22:43; freshness should be verified.

Geography

Data sourced from donors across Asian, Black, and White populations.