Robust joint score tests in the application of DNA methylation data analysis

BMC Bioinformatics
Xuan LiWeiliang Qiu

Abstract

Recently differential variability has been showed to be valuable in evaluating the association of DNA methylation to the risks of complex human diseases. The statistical tests based on both differential methylation level and differential variability can be more powerful than those based only on differential methylation level. Anh and Wang (2013) proposed a joint score test (AW) to simultaneously detect for differential methylation and differential variability. However, AW's method seems to be quite conservative and has not been fully compared with existing joint tests. We proposed three improved joint score tests, namely iAW.Lev, iAW.BF, and iAW.TM, and have made extensive comparisons with the joint likelihood ratio test (jointLRT), the Kolmogorov-Smirnov (KS) test, and the AW test. Systematic simulation studies showed that: 1) the three improved tests performed better (i.e., having larger power, while keeping nominal Type I error rates) than the other three tests for data with outliers and having different variances between cases and controls; 2) for data from normal distributions, the three improved tests had slightly lower power than jointLRT and AW. The analyses of two Illumina HumanMethylation27 data sets GSE37020 and GSE2...Continue Reading

References

Apr 4, 2009·The Journal of Immunology : Official Journal of the American Association of Immunologists·Thalie DevosseMarc Parmentier
Mar 12, 2010·Genome Research·Andrew E TeschendorffMartin Widschwendter
Jul 23, 2013·The Journal of Biological Chemistry·Mustafa N YaziciogluKatherine A High
Sep 14, 2013·Epigenetics : Official Journal of the DNA Methylation Society·Sanja A FarkasTorbjörn K Nilsson
Jul 6, 2014·BMC Bioinformatics·Simone WahlMatthias Schmid
Dec 24, 2015·Tumour Biology : the Journal of the International Society for Oncodevelopmental Biology and Medicine·E KudelaJ Danko
Apr 23, 2016·BMC Bioinformatics·Andrew E TeschendorffMartin Widschwendter

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Citations

Oct 16, 2021·European Journal of Epidemiology·James R StaleyKate Tilling

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Datasets Mentioned

BETA
GSE20080
GSE107080

Software Mentioned

jointLRT
R
iAW

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