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

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.