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

	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Biochemistry, biophysics & molecular biology Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences; Systems Biomedicine
	To cite this reference:	http://hdl.handle.net/10993/41428

Title :	Testing for association between RNA-Seq and high-dimensional data
Language :	English
Author, co-author :	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]
Publication date :	8-Mar-2016
Journal title :	BMC Bioinformatics
Publisher :	BioMed Central
Volume :	17
Pages :	118
Peer reviewed :	Yes (verified by ORBilu)
Audience :	International
ISSN :	1471-2105
City :	London
Country :	United Kingdom
Keywords :	[en] high-dimensional ; overdispersion ; negative binomial ; global test ; integration ; RNA-seq
Abstract :	[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.
Funders :	Department of Epidemiology and Biostatistics, VU University Medical Center
Target :	Researchers
Permalink :	http://hdl.handle.net/10993/41428
DOI :	10.1186/s12859-016-0961-5
Other URL :	https://doi.org/10.1186/s12859-016-0961-5
Mentions required by the publisher for OA :	The original publication is available from BMC Bioinformatics (open access).
Commentary :	https://bioconductor.org/packages/globalSeq/

	File(s) associated to this reference
	Fulltext file(s): File Commentary Version Size Access Open access Rauschenberger2016_globalSeq.pdf Publisher postprint 1.1 MB View/Open Additional material(s): File Commentary Size Access Open access Rauschenberger2016_Appendix.pdf 486.77 kB View/Open

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