naa a22 4500 510787479 CHVBK 20180411083307.0 cr unu---uuuuu 180411e20131201xx s 000 0 eng 10.1007/s12041-013-0282-7 doi (NATIONALLICENCE)springer-10.1007/s12041-013-0282-7 An estimating function approach to linkage heterogeneity [Elektronische Daten] [HE GAO, YING ZHOU, WEIJUN MA, HAIDONG LIU, LINAN ZHAO] 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. Indian Academy of Sciences, 2013 linkage heterogeneity nationallicence likelihood ratio nationallicence power nationallicence recombination fraction nationallicence test nationallicence GAO HE Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut ZHOU YING Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut MA WEIJUN Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut LIU HAIDONG Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut ZHAO LINAN Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut Journal of Genetics Springer India 92/3(2013-12-01), 413-421 0022-1333 92:3<413 2013 92 12041 https://doi.org/10.1007/s12041-013-0282-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s12041-013-0282-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- GAO HE Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut NATIONALLICENCE 700 1- ZHOU YING Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut NATIONALLICENCE 700 1- MA WEIJUN Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut NATIONALLICENCE 700 1- LIU HAIDONG Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut NATIONALLICENCE 700 1- ZHAO LINAN Department of Statistics, School of Mathematical Sciences, Heilongjiang University, 150080, Harbin, People's Republic of China aut NATIONALLICENCE 773 0- Journal of Genetics Springer India 92/3(2013-12-01), 413-421 0022-1333 92:3<413 2013 92 12041 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer