A powerful approach for association analysis incorporating imprinting effects

Bioinformatics. 2011 Sep 15;27(18):2571-7. doi: 10.1093/bioinformatics/btr443. Epub 2011 Jul 28.

Abstract

Motivation: For a diallelic marker locus, the transmission disequilibrium test (TDT) is a simple and powerful design for genetic studies. The TDT was originally proposed for use in families with both parents available (complete nuclear families) and has further been extended to 1-TDT for use in families with only one of the parents available (incomplete nuclear families). Currently, the increasing interest of the influence of parental imprinting on heritability indicates the importance of incorporating imprinting effects into the mapping of association variants.

Results: In this article, we extend the TDT-type statistics to incorporate imprinting effects and develop a series of new test statistics in a general two-stage framework for association studies. Our test statistics enjoy the nature of family-based designs that need no assumption of Hardy-Weinberg equilibrium. Also, the proposed methods accommodate complete and incomplete nuclear families with one or more affected children. In the simulation study, we verify the validity of the proposed test statistics under various scenarios, and compare the powers of the proposed statistics with some existing test statistics. It is shown that our methods greatly improve the power for detecting association in the presence of imprinting effects. We further demonstrate the advantage of our methods by the application of the proposed test statistics to a rheumatoid arthritis dataset.

Contact: wingfung@hku.hk

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Arthritis, Rheumatoid / genetics*
  • Child
  • Genetic Testing*
  • Genome-Wide Association Study
  • Genomic Imprinting*
  • Humans
  • Models, Genetic
  • Nuclear Family
  • Parents
  • Polymorphism, Genetic
  • Reproducibility of Results