cydar

cydar identifies differentially abundant cell populations in mass cytometry datasets to compare biological conditions.

Key Features:

• Hypersphere assignment: cydar assigns cells to multidimensional hyperspheres to represent local cell populations.
• Statistical testing: cydar performs statistical tests to detect significant differences in hypersphere-associated cell counts between conditions.
• Spatial false discovery rate control: cydar controls the spatial false discovery rate across hypersphere tests to reduce erroneous identifications.

Scientific Applications:

• Investigating immune responses: comparing cell population abundances across health and disease states to characterize immune changes.
• Studying cellular heterogeneity in cancer: identifying differentially abundant cell populations that may indicate biomarkers or therapeutic targets.
• Analyzing developmental biology datasets: assessing changes in cell population dynamics across developmental stages.
• Benchmarking and method comparison: demonstrated superior performance in simulations relative to other existing approaches.

Methodology:

Assigning cells to multidimensional hyperspheres, performing statistical tests to compare conditions, and controlling the spatial false discovery rate.