Palo

Palo optimizes color palette assignments in a spatially-aware manner to improve visualization of clusters in single-cell and spatial genomic datasets.

Key Features:

• Spatially-aware palette optimization: Considers spatial adjacency when assigning colors to clusters on two-dimensional plots to reduce visually similar colors among neighboring clusters.
• Neighbor-pair detection: Identifies pairs of clusters that are spatially neighboring each other within plots.
• Distinct color assignment: Assigns visually distinct colors specifically to neighboring cluster pairs to improve differentiation.
• Support for cells and spots: Operates on clusters of cells or spatial spots in single-cell and spatial genomic datasets.
• R package implementation: Implemented as an R package for integration into analysis workflows.

Scientific Applications:

• Visualization of single-cell and spatial genomic data: Enhances clarity of cluster visualizations in real-world single-cell and spatial genomic datasets.
• Exploratory cluster analysis: Facilitates identification and differentiation of clusters on two-dimensional plots during exploratory data analysis.
• Spatial relationship interpretation: Aids interpretation of complex spatial relationships by making adjacent clusters visually distinct.

Methodology:

Palo identifies spatially neighboring cluster pairs within two-dimensional plots and assigns visually distinct colors to those neighboring pairs; the method is implemented as an R package.