voom: precision weights unlock linear model analysis tools for RNA-seq read counts

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• The University of Melbourne (hdl.handle.net)Preprint · PDF
• European Bioinformatics Institute (ncbi.nlm.nih.gov)Preprint · Web page

Abstract

New normal linear modeling strategies are presented for analyzing read counts from RNA-seq experiments. The voom method estimates the mean-variance relationship of the log-counts, generates a precision weight for each observation and enters these into the limma empirical Bayes analysis pipeline. This opens access for RNA-seq analysts to a large body of methodology developed for microarrays. Simulation studies show that voom performs as well or better than count-based RNA-seq methods even when the data are generated according to the assumptions of the earlier methods. Two case studies illustrate the use of linear modeling and gene set testing methods.