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A method for identifying genes related to a quantitative trait, incorporating multiple siblings and missing parents
Author(s) -
Kistner Emily O.,
Weinberg Clarice R.
Publication year - 2005
Publication title -
genetic epidemiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.301
H-Index - 98
eISSN - 1098-2272
pISSN - 0741-0395
DOI - 10.1002/gepi.20084
Subject(s) - trait , quantitative trait locus , linkage (software) , genetic association , imputation (statistics) , polytomous rasch model , population , genetics , missing data , biology , nuclear family , genotype , statistics , mathematics , item response theory , computer science , gene , medicine , single nucleotide polymorphism , environmental health , sociology , anthropology , programming language , psychometrics
When studying either qualitative or quantitative traits, tests of association in the presence of linkage are necessary for fine‐mapping. In a previous report (Kistner and Weinberg [2004] Genet Epidemiol 27:33–42), we suggested a polytomous logistic approach to testing linkage and association between a di‐allelic marker and a quantitative trait locus, using genotyped triads, consisting of an individual whose quantitative trait has been measured and his or her two parents. Here we extend that approach to incorporate marker information from entire nuclear families. By computing a weighted score function instead of a maximum likelihood test, we allow for both an unspecified correlation structure between siblings and “informative” family size (Williamson et al. [2003] Biometrics 59:36–42). Both this approach and our original approach allow for population admixture by conditioning on parental genotypes. The proposed method allows for missing parental genotype data through a multiple imputation procedure. We use simulations based on a population with admixture to compare our method to a popular non‐parametric family‐based association test (FBAT), testing the null of no association in the presence of linkage (Rabinowitz and Laird [2000] Human Hered 50:211–223). Genet. Epidemiol. 2005. Published 2005 Wiley‐Liss, Inc.