title: Multivariable conditional analysis for complex trait and its components.
abstract: Methods of multivariable conditional analysis were proposed for analyzing contribution of component traits to complex target trait based on mixed linear model approaches. The contribution ratio and the contributed genetic effect were defined. The contribution ratio could measure the proportion of genetic variation of the given component trait on the target trait. The contributed genetic effect could quantify genetic effect of the given component traits contributed to the target trait. A worked example from the cotton data is given to illustrate the application of the new methods for analyzing the contribution of three yield components to lint yield.
authors.affiliation: Department of Agronomy, Zhejiang University, Hangzhou 310029, China.
authors.forename: Yong-Xian
authors.initials: YX
authors.lastname: Wen
authors.forename: Jun
authors.initials: J
authors.lastname: Zhu
mesh_terms: D001947:Breeding; D014644:Genetic Variation; D003368:Gossypium / Q000235:genetics* / Q000254:growth & development; D016014:Linear Models; D008957:Models, Genetic; D015999:Multivariate Analysis; D040641:Quantitative Trait Loci / Q000235:genetics*; D012639:Seeds / Q000235:genetics / Q000254:growth & development