Gene expression variability and the analysis of large-scale RNA-seq studies with the MDSeq.

ABSTRACT: Rapidly decreasing cost of next-generation sequencing has led to the recent availability of large-scale RNA-seq data, that empowers the analysis of gene expression variability, in addition to gene expression means. In this paper, we present the MDSeq, based on the coefficient of dispersion, to provide robust and computationally efficient analysis of both gene expression means and variability on RNA-seq counts. The MDSeq utilizes a novel reparametrization of the negative binomial to provide flexible generalized linear models (GLMs) on both the mean and dispersion. We address challenges of analyzing large-scale RNA-seq data via several new developments to provide a comprehensive toolset that models technical excess zeros, identifies outliers efficiently, and evaluates differential expression

SUBMITTER: Ran D 

PROVIDER: S-EPMC5737414 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature