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SCPattern: A statistical approach to identify and classify expression changes in single cell RNA-seq experiments with ordered conditions
Motivation: With the development of single cell RNA-seq (scRNA-seq) technology, scRNA-seq experiments with ordered conditions (e.g. time-course) are becoming common. Methods developed for analyzing ordered bulk RNA-seq experiments are not applicable to scRNA-seq, since their distributional assumptions are often violated by additional heterogeneities prevalent in scRNA-seq. Here we present SCPattern - an empirical Bayes model to characterize genes with expression changes in ordered scRNA-seqdoi:10.1101/046110 fatcat:cvqfon4o5racnglz3ngmnbjxvm