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bioRxiv · 10.1101/040170

variancePartition: Interpreting drivers of variation in complex gene expression studies

Gabriel E Hoffman·Eric E Schadt
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Abstract

As genomics studies become more complex and consider multiple sources of biological and technical variation, characterizing these drivers of variation becomes essential to understanding disease biology and regulatory genetics. We describe a statistical and visualization framework, variancePartition, to prioritize drivers of variation with a genome-wide summary, and identify genes that deviate from the genome-wide trend. variancePartition enables rapid interpretation of complex gene expression studies and is applicable to many genomics assays.

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Gabriel E Hoffman, Eric E Schadt. 2016-02-19. variancePartition: Interpreting drivers of variation in complex gene expression studies. https://doi.org/10.1101/040170

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