
In the past decade phenomenal progress has been made in molecular and statistical genetic methods for localizing quantitative trait loci. Because of these advances, we can anticipate a long period of active genetic research in which the genes influencing human quantitative variability will be mapped and their effects accurately evaluated. Here, we review the current state of the science in statistical genetic methods for quantitative trait linkage analysis. In particular, we detail a variance component-based framework for localizing quantitative trait loci and for accurately estimating their relative effect sizes. Attention is paid to the optimal design of human family studies for localizing genes of small to moderate effect. In addition, methods and strategies are described for dealing with the most important complications of quantitative variation, including the assessment of genotype x environment interaction and epistasis.
Likelihood Functions, Genotype, Models, Genetic, Chromosome Mapping, Genetic Variation, Reproducibility of Results, Environment, Pedigree, Quantitative Trait, Heritable, Bias, Gene Frequency, Data Interpretation, Statistical, Multivariate Analysis, Prevalence, Humans, Lod Score
Likelihood Functions, Genotype, Models, Genetic, Chromosome Mapping, Genetic Variation, Reproducibility of Results, Environment, Pedigree, Quantitative Trait, Heritable, Bias, Gene Frequency, Data Interpretation, Statistical, Multivariate Analysis, Prevalence, Humans, Lod Score
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