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Adaptive Transmission Disequilibrium Test for Family Trio Design

Author

Listed:
  • Yuan Min

    (University of Science and Technology of China)

  • Tian Xin

    (National Heart, Lung and Blood Institute)

  • Zheng Gang

    (National Heart, Lung and Blood Institute)

  • Yang Yaning

    (University of Science and Technology of China)

Abstract

The transmission disequilibrium test (TDT) is a standard method to detect association using family trio design. It is optimal for an additive genetic model. Other TDT-type tests optimal for recessive and dominant models have also been developed. Association tests using family data, including the TDT-type statistics, have been unified to a class of more comprehensive and flexable family-based association tests (FBAT). TDT-type tests have high efficiency when the genetic model is known or correctly specified, but may lose power if the model is mis-specified. Hence tests that are robust to genetic model mis-specification yet efficient are preferred. Constrained likelihood ratio test (CLRT) and MAX-type test have been shown to be efficiency robust. In this paper we propose a new efficiency robust procedure, referred to as adaptive TDT (aTDT). It uses the Hardy-Weinberg disequilibrium coefficient to identify the potential genetic model underlying the data and then applies the TDT-type test (or FBAT for general applications) corresponding to the selected model. Simulation demonstrates that aTDT is efficiency robust to model mis-specifications and generally outperforms the MAX test and CLRT in terms of power. We also show that aTDT has power close to, but much more robust, than the optimal TDT-type test based on a single genetic model. Applications to real and simulated data from Genetic Analysis Workshop (GAW) illustrate the use of our adaptive TDT.

Suggested Citation

  • Yuan Min & Tian Xin & Zheng Gang & Yang Yaning, 2009. "Adaptive Transmission Disequilibrium Test for Family Trio Design," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-22, June.
    • Handle: RePEc:bpj:sagmbi:v:8:y:2009:i:1:n:30
    DOI: 10.2202/1544-6115.1451
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    References listed on IDEAS

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    1. Robert Sladek & Ghislain Rocheleau & Johan Rung & Christian Dina & Lishuang Shen & David Serre & Philippe Boutin & Daniel Vincent & Alexandre Belisle & Samy Hadjadj & Beverley Balkau & Barbara Heude &, 2007. "A genome-wide association study identifies novel risk loci for type 2 diabetes," Nature, Nature, vol. 445(7130), pages 881-885, February.
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    Cited by:

    1. Yuan Min & Pan Xiaoqing & Yang Yaning, 2015. "Bayes factors based on robust TDT-type tests for family trio design," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(3), pages 253-264, June.

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