Mapping Quantitative Trait Loci Using Multiple Families of Line Crosses
Author(s) -
Shizhong Xu
Publication year - 1998
Publication title -
genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.792
H-Index - 246
eISSN - 1943-2631
pISSN - 0016-6731
DOI - 10.1093/genetics/148.1.517
Subject(s) - linkage (software) , quantitative trait locus , trait , biology , genetics , random effects model , statistics , substitution (logic) , monte carlo method , population , variance (accounting) , genetic linkage , mathematics , gene , computer science , medicine , meta analysis , demography , accounting , sociology , business , programming language
To avoid a loss in statistical power as a result of homozygous individuals being selected as parents of a mapping population, one can use multiple families of line crosses for quantitative trait genetic linkage analysis. Two strategies of combining data are investigated: the fixed-model and the random-model strategies. The fixed-model approach estimates and tests the average effect of gene substitution for each parent, while the random-model approach treats each effect of gene substitution as a random variable and directly estimates and tests the variance of gene substitution. Extensive Monte Carlo simulations verify that the two strategies perform equally well, although the random model is preferable in combining data from a large number of families. Simulations also show that there may be an optimal sampling strategy (number of families vs. number of individuals per family) in which QTL mapping reaches its maximum power and minimum estimation error. Deviation from the optimal strategy reduces the efficiency of the method.
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