scDotPlot

scDotPlot performs hierarchical clustering analysis and adds annotations to columns and/or rows of single-cell RNA-seq dot plots to examine relationships between cell groupings and marker gene expression.

Key Features:

• Hierarchical clustering analysis: Performs hierarchical clustering on single-cell RNA-seq dot plot data as a unified analytical approach.
• Annotation integration: Adds annotations to columns and/or rows of scRNA-seq dot plots.
• Multiple data formats: Works with SingleCellExperiment objects, Seurat objects, and data frames.

Scientific Applications:

• Cell clustering analysis: Examines relationships between cell groupings such as clusters and marker gene expression in single-cell RNA-seq data.
• Marker gene visualization: Generates annotated dot plots to visualize marker gene expression patterns across cell populations.

Methodology:

Hierarchical clustering analysis is performed on single-cell RNA-seq dot plot data with annotation addition to columns and/or rows.