Investigate the expression of specific marker genes across single-cell RNA-seq data using customizable ridge plots, violin plots, and UMAP projections.

Marker expression analysis in single-cell RNA-seq datasets provides an in-depth view of gene expression across individual cells. Researchers can categorize cells based on clustering annotations, variables, or latent variables, and customize visualizations with color scales and group palettes. Using tools like ridge plots, violin plots, and UMAPs, users can explore cellular heterogeneity and functional diversity within their samples. This analysis facilitates the identification of cell populations with varying gene expression levels, offering insights into cellular states, developmental stages, or disease conditions.