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

被引：2
|
作者：
Rauschenberger, Armin [1 ]
Jonker, Marianne A. [1 ]
van de Wiel, Mark A. [1 ,2 ]
Menezes, Renee X. [1 ]
机构：
[1] Vrije Univ Amsterdam, Med Ctr, Dept Epidemiol & Biostat, NL-1007 MB Amsterdam, Netherlands
[2] Vrije Univ Amsterdam, Dept Math, NL-1081 HV Amsterdam, Netherlands
来源：
BMC BIOINFORMATICS | 2016年 / 17卷
关键词：
High-dimensional; Overdispersion; Negative binomial; Global test; Integration; RNA-Seq; DIFFERENTIAL EXPRESSION ANALYSIS; MOLECULAR PROFILES; SCORE TESTS; TRANSCRIPTOME; GENES;
D O I：
10.1186/s12859-016-0961-5
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
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.
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页数：8
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