Testing for association between RNA-Seq and high-dimensional data

Abstract

BACKGROUND: Testing for association between RNA-Seq and other genomic data is challenging due to high variability of the former and high dimensionality of the latter. RESULTS: Using the negative binomial distribution and a random-effects model, we develop an omnibus test that overcomes both difficulties. It may be conceptualised as a test of overall significance in regression analysis, where the response variable is overdispersed and the number of explanatory variables exceeds the sample size. CONCLUSIONS: The proposed test can detect genetic and epigenetic alterations that affect gene expression. It can examine complex regulatory mechanisms of gene expression. The R package globalSeq is available from Bioconductor.