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

Armin Rauschenberger, Marianne A. Jonker, Mark A. van de Wiel, Ren�e X. Menezes*

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Article number118
JournalBMC Bioinformatics
Issue number1
Publication statusPublished - 2016
Externally publishedYes


  • Global test
  • High-dimensional
  • Integration
  • Negative binomial
  • Overdispersion
  • RNA-Seq


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