CytoMDS

CytoMDS implements low-dimensional visualization of cytometry samples to visually assess distances between them and identify quality issues such as batch effects, outlier samples, or sample clusters aligning with experimental design.

Key Features:

• Earth Mover's Distance (EMD) Integration: Computes pairwise sample distances using the Wasserstein metric, adapted for cytometry data distributions.
• Multi Dimensional Scaling (MDS) Projection: Projects high-dimensional cytometry sample distances into a low-dimensional space for visualization.
• MDS Quality Diagnostics: Provides diagnostic tools to check the quality and reliability of the MDS projection.
• Axis Interpretation Tools: Provides tools to help interpret the biological meaning of the projection axes.

Scientific Applications:

• Quality Control in Cytometry Studies: Identifies batch effects and outlier samples in cytometry datasets through distance-based visualization.
• Experimental Design Validation: Checks whether sample clusters in the projection align with expected experimental conditions or groupings.

Methodology:

The CytoMDS algorithm combines Earth Mover's Distance (EMD), also known as the Wasserstein metric, with Multi Dimensional Scaling (MDS) for low-dimensional projection of cytometry samples.