EconPapers    
Economics at your fingertips  
 

Differential methylation tests of regulatory regions

Ryu Duchwan, Xu Hongyan (), George Varghese, Su Shaoyong, Wang Xiaoling, Shi Huidong and Podolsky Robert H.
Additional contact information
George Varghese: Department of Biostatistics and Epidemiology, Augusta University, Augusta, GA, USA
Wang Xiaoling: Georgia Prevention Institute, Department of Pediatrics, Augusta University, Augusta, GA, USA
Shi Huidong: AU Cancer Center, Department of Biochemistry and Molecular Biology, Augusta University, Augusta, GA, USA
Podolsky Robert H.: Department of Family Medicine and Public Health Sciences, Wayne State University, Detroit, MI, USA

Statistical Applications in Genetics and Molecular Biology, 2016, vol. 15, issue 3, 237-251

Abstract: Differential methylation of regulatory elements is critical in epigenetic researches and can be statistically tested. We developed a new statistical test, the generalized integrated functional test (GIFT), that tests for regional differences in methylation based on the methylation percent at each CpG site within a genomic region. The GIFT uses estimated subject-specific profiles with smoothing methods, specifically wavelet smoothing, and calculates an ANOVA-like test to compare the average profile of groups. In this way, possibly correlated CpG sites within the regulatory region are compared all together. Simulations and analyses of data obtained from patients with chronic lymphocytic leukemia indicate that GIFT has good statistical properties and is able to identify promising genomic regions. Further, GIFT is likely to work with multiple different types of experiments since different smoothing methods can be used to estimate the profiles of data without noise. Matlab code for GIFT and sample data are available at http://www.augusta.edu/mcg/biostatepi/people/software/gift.html.

Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://doi.org/10.1515/sagmb-2015-0037 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:sagmbi:v:15:y:2016:i:3:p:237-251:n:3

Ordering information: This journal article can be ordered from
https://www.degruyter.com/view/j/sagmb

DOI: 10.1515/sagmb-2015-0037

Access Statistics for this article

Statistical Applications in Genetics and Molecular Biology is currently edited by Michael P. H. Stumpf

More articles in Statistical Applications in Genetics and Molecular Biology from De Gruyter
Bibliographic data for series maintained by Peter Golla ().

 
Page updated 2021-05-07
Handle: RePEc:bpj:sagmbi:v:15:y:2016:i:3:p:237-251:n:3