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A unified framework for transmission-disequilibrium test analysis of discrete and continuous traits
Ying Liu1, David Tritchler, Shelley B Bull
1Department of Public Health Sciences, University of Toronto, Toronto, Ontario, Canada.
Abstract:
This paper presents a unified framework for transmission-disequilibrium tests for discrete and continuous traits. A conditional score test is derived that maximizes power to detect small effects for any exponential family distribution, which includes binary and normal distributions, and distributions that are skewed or have non-normal kurtosis. The specific distributional form need not be specified, and the method applies to sibships of arbitrary size. Formulas for the distribution of the test statistic are given for models including complex genetic effects (additive, dominant, and recessive gene action), covariates, multiple gene models including gene-gene interactions or heterogeneity, and gene-environment interactions. We develop refinements of our method for trait-based sampling designs and multiple siblings that can have dramatic effects on power.
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