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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.
Using the negative binomial distribution and a random effects model, we developed 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.
The proposed method can detect genetic and epigenetic alterations that affect gene expression. It can examine complex regulatory mechanisms of gene expression.
omnibus
tests entire covariate sets
proprius
shows individual contributions
cursus
analyses the whole genome
The following command opens the vignette:
utils::vignette("globalSeq")
A Rauschenberger, MA Jonker, MA van de Wiel, and RX Menezes (2016).
"Testing for association between RNA-Seq and high-dimensional data",
BMC Bioinformatics. 17:118.
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(open access)
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