Testing for association between RNA-Seq and high-dimensional data
English
Rauschenberger, Armin[VU University Medical Center, Amsterdam, The Netherlands > Department of Epidemiology and Biostatistics]
Jonker, Marianne A.[VU University Medical Center, Amsterdam, The Netherlands > Department of Epidemiology and Biostatistics]
van de Wiel, Mark A.[VU University Medical Center, Amsterdam, The Netherlands > Department of Epidemiology and Biostatistics > > ; VU University, Amsterdam, The Netherlands > Department of Mathematics]
Menezes, Renée X.[VU University Medical Center, Amsterdam, The Netherlands > Department of Epidemiology and Biostatistics]
[en] high-dimensional ; overdispersion ; negative binomial ; global test ; integration ; RNA-seq
[en] 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.
Department of Epidemiology and Biostatistics, VU University Medical Center