MOCCASIN: A method for correcting for known and unknown confounders in RNA splicing analysis

Abstract

While the effects of confounders on gene expression analysis have been extensively studied there is a lack of equivalent analysis and tools for RNA splicing analysis. Here we assess the effect of confounders in two large public RNA-Seq datasets (TARGET, ENCODE), develop a new method, MOCCASIN, to correct the effect of both known and unknown confounders on RNA splicing quantification, and demonstrate MOCCASINs effectiveness on both synthetic and real data.