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PMID: 15583426 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

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

Human heredity ·Vol. 57 ·No. 4 ·2004-00-00 ·Pages 200-6

Burkett K, McNeney B, Graham J

Abstract

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.

MeSH Terms
Algorithms Computer Simulation Data Interpretation, Statistical Genotype Haplotypes Likelihood Functions Linear Models Polymorphism, Single Nucleotide
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Burkett Kelly
UBC McDonald Research Laboratories/iCAPTURE Centre, St Paul's Hospital, Vancouver, Canada.
McNeney Brad
Graham Jinko
Article Info
Journal
Human heredity
Abbr.
Hum Hered
ISSN
0001-5652
Published
2004-00-00
Pages
200-6
Language
English
Region
Switzerland
NLM ID
0200525
Subset
IM
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