COMPARE, an ultra-fast and robust suite for multiparametric screening, identifies phenotypic drug responses in acute myeloid leukemia

Multiparametric phenotypic screening of cells, for example assessing their responses to small molecules or knockdown/knockout of specific genes, is a powerful approach to understanding cellular systems and identifying potential new therapeutic strategies. However, automated tools for analyzing similarities and differences between a large number of tested conditions have not been readily available. Methods designed for clustering cells cannot identify differences between samples effectively. We introduce COMPARE for ultra-fast and robust analysis of multiparametric high-throughput screening. Applying a mass-aware gridding algorithm using hypercubes, COMPARE performs automatic and effective similarity comparison for hundreds to thousands of tests and provides information about the treatment effect. Particularly for screening data, COMPARE is equipped with modules to remove various sources of bias. Benchmarking tests show that COMPARE can circumvent batch effects and perform a similarity analysis substantially faster than conventional analysis tools. Applying COMPARE to high-throughput flow cytometry screening data, we were able to distinguish subtle phenotypic drug responses in a human sample and a genetically engineered mouse model with acute myeloid leukemia (AML). COMPARE revealed groups of drugs with similar responses even though their mechanisms are distinct from each other. In another screening, COMPARE effectively circumvented batch effects and grouped samples from AML and myelodysplastic syndrome (MDS) patients using clinical flow cytometry data.