Linkage strategies for analyzing complex traits in man differ from the more classical Mendelian linkage methods in that no knowledge of the inheritance pattern of the trait or the characteristics of the responsible gene are required. The so-called non-parametric statistical methods developed to study complex traits derive their genetic information from IBD allele sharing among relatives. The choice of which method to use depends on the nature and prevalence of the phenotype. If the trait of interest can be measured quantitatively that will provide more power to detect linkage than dichotomous versions of the same trait. For quantitative traits or common discrete traits, variance component methods in large pedigrees will provide the most power. For discrete traits with a prevalence of less than 10%, affected relative pair methods are most efficient. Ascertain- ment will maximize power for a single focal trait, but should be conducted in a systematic manner with identifiable probands. For studies of multiple related traits that are common or quantitative, random sampling is most efficient. While candidate genes of known functional relevance should be tested, a complete genome screen with evenly-spaced, highly polymorphic markers presents the greatest chance of success. Positional candidate regions identified through such a screen may then be followed up with family-based disequilibrium analyses for finer QTL mapping.
ASJC Scopus subject areas
- Behavioral Neuroscience