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March 2013 Robust partial likelihood approach for detecting imprinting and maternal effects using case-control families
Jingyuan Yang, Shili Lin
Ann. Appl. Stat. 7(1): 249-268 (March 2013). DOI: 10.1214/12-AOAS577


Genomic imprinting and maternal effects are two epigenetic factors that have been increasingly explored for their roles in the etiology of complex diseases. This is part of a concerted effort to find the “missing heritability.” Accordingly, statistical methods have been proposed to detect imprinting and maternal effects simultaneously based on either a case-parent triads design or a case-mother/control-mother pairs design. However, existing methods are full-likelihood based and have to make strong assumptions concerning mating type probabilities (nuisance parameters) to avoid overparametrization. In this paper we propose to augment the two popular study designs by combining them and including control-parent triads, so that our sample may contain a mixture of case-parent/control-parent triads and case-mother/control-mother pairs. By matching the case families with control families of the same structure and stratifying according to the familial genotypes, we are able to derive a partial likelihood that is free of the nuisance parameters. This renders unnecessary any unrealistic assumptions and leads to a robust procedure without sacrificing power. Our simulation study demonstrates that our partial likelihood method has correct type I error rate, little bias and reasonable power under a variety of settings.


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Jingyuan Yang. Shili Lin. "Robust partial likelihood approach for detecting imprinting and maternal effects using case-control families." Ann. Appl. Stat. 7 (1) 249 - 268, March 2013.


Published: March 2013
First available in Project Euclid: 9 April 2013

zbMATH: 06171271
MathSciNet: MR3086418
Digital Object Identifier: 10.1214/12-AOAS577

Keywords: case-mother/control-mother pairs , case-parent/control-parent triads , genomic imprinting , maternal effect , mating type probabilities

Rights: Copyright © 2013 Institute of Mathematical Statistics

Vol.7 • No. 1 • March 2013
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