A note on inference of trait associations with SNP haplotypes and other attributes in generalized linear models.
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.
Burkett
Kelly
K
UBC McDonald Research Laboratories/iCAPTURE Centre, St Paul's Hospital, Vancouver, Canada.
McNeney
Brad
B
Graham
Jinko
J
D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005838:Genotype; D006239:Haplotypes; D016013:Likelihood Functions; D016014:Linear Models; D020641:Polymorphism, Single Nucleotide