Bayesian QTL mapping using skewed Student-tdistributions

TR Number
Date
2002-01-15
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract

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.

Description
Keywords
Citation
Genetics Selection Evolution. 2002 Jan 15;34(1):1-21