A regression model approach to enable cell morphology correction in high-throughput flow cytometry

Abstract

Large variations in cell size and shape can undermine traditional gating methods for analyzing flow cytometry data. Correcting for these effects enables analysis of high-throughput data sets, including >5000 yeast samples with diverse cell morphologies