von Rohr Peter, Hoeschele Ina
Departments of Dairy Science and Statistics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0315, USA.
Genet Sel Evol. 2002 Jan-Feb;34(1):1-21. doi: 10.1186/1297-9686-34-1-1.
In most QTL mapping studies, phenotypes are assumed to follow normal distributions. Deviations from this assumption may lead to detection of false positive QTL. To improve the robustness of Bayesian QTL mapping methods, the normal distribution for residuals is replaced with a skewed Student-t distribution. The latter distribution is able to account for both heavy tails and skewness, and both components are each controlled by a single parameter. The Bayesian QTL mapping method using a skewed Student-t distribution is evaluated with simulated data sets under five different scenarios of residual error distributions and QTL effects.
在大多数数量性状基因座（QTL）定位研究中，假定表型服从正态分布。偏离这一假设可能会导致检测到假阳性QTL。为了提高贝叶斯QTL定位方法的稳健性，将残差的正态分布替换为偏态学生t分布。后一种分布能够兼顾厚尾和偏态，且这两个分量均由单个参数控制。使用偏态学生t分布的贝叶斯QTL定位方法在残差误差分布和QTL效应的五种不同情形下通过模拟数据集进行评估。
