A note on inference of trait associations with SNP haplotypes and other attributes in generalized linear models

被引:25
作者
Burkett, K
McNeney, B
Graham, J
机构
[1] Simon Fraser Univ, Dept Stat & Actuarial Sci, Burnaby, BC V5A 1S6, Canada
[2] St Pauls Hosp, UBC McDonald Res Lab iCAPTURE Ctr, Vancouver, BC V6Z 1Y6, Canada
关键词
haplotype phase; association study; maximum likelihood; EM algorithm; missing data; variance estimates;
D O I
10.1159/000081447
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Recently, Lake et al. [Human Heredity 2003; 55: 56-65] have proposed an approach based on the EM algorithm for maximum-likelihood inference of trait associations with haplotypes and environmental cofactors in generalized linear models. In this short report, we describe an extension to accommodate missing SNP genotype information. We also discuss differences in the calculation of standard errors between their implementation and our own. Finally, we present results indicating that inference is robust to low levels of dependence between haplotypes and nongenetic factors, but that biased inference can result when there is moderate to strong dependence. Overall, the method is found to perform well in the models we considered. Copyright (C) 2004 S. Karger AG, Basel.
引用
收藏
页码:200 / 206
页数:7
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