Statistical models for the linkage analysis of the quantitative trait

초록

We suggested statistical models for linkage analysis of quantitative trait locus (QTL) with pedigree data. The proposed models involve mixed models based on the adjusted Haseman-Elston model and allow random effects. We considered a response variable as sibship sample mean corrected cross-product of quantitative trait (QT) proposed by Wang et al (2001). The proposed models consist of a random effect for correlation among sib-pairs having one sibling in common, and one for the correlation among siblings from the same parents. In addition, we considered several types of adjusting trait factors included in the proposed models. The proposed models were applied to the analysis of the Genetic Analysis Workshop 12 (GAW12) simulated dataset for a QT which contains 38,850 observations and 1,150 pedigrees. A model after adjusting for each QT (or QT2) of siblings yielded good power for detecting linkage for these datasets. Both random effects models showed similar performance. The plots of residuals followed asymptotically normal distribution when using the proposed models. The proposed models seem not only quite useful in detecting linkage for the QT but also quite flexible to use. They can handle a wide class of correlation structures. Models with a more general class of covariance structure are desirable.