Bayesian QTL mapping using skewed Student-t distributions
Open Access
- 15 January 2002
- journal article
- Published by Springer Nature in Genetics Selection Evolution
- Vol. 34 (1) , 1-21
- https://doi.org/10.1186/1297-9686-34-1-1
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.Keywords
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