An estimating function approach to linkage heterogeneity
He Gao Ying Zhou Weijun Ma Haidong Liu Linan Zhao
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Testing linkage heterogeneity between two loci is an important issue in genetics. Currently, there are four methods (K-test, A-test, B-test and D-test) for testing linkage heterogeneity in linkage analysis, which are based on the likelihood-ratio test. Among them, the commonly used methods are the K-test and A-test. In this paper, we present a novel test method which is different from the above four tests, called G-test. The new test statistic is based on estimating function, possessing a theoretic asymptotic distribution, and therefore demonstrates its own advantages. The proposed test is applied to analyse a real pedigree dataset. Our simulation results also indicate that the G-test performs well in terms of power of testing linkage heterogeneity and outperforms the current methods to some degree.
He Gao1 2 Ying Zhou1 Weijun Ma1 Haidong Liu1 Linan Zhao1
Volume 102, 2023
Continuous Article Publishing mode
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