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Bayesian hierarchical regression models for detecting QTLs in plant experiments |
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| Authors: | Edward L Boone Susan J Simmons Haikun Bao Ann E Stapleton |
| Institution: | 1. Department of Statistical Sciences and Operations Research , Virginia Commonwealth University , Richmond , VA , USA;2. Department of Mathematics and Statistics , University of North Carolina Wilmington , Wilmington , NC , USA;3. Department of Epidemiology and Biostatistics , University of South Carolina , Columbia , SC , USA;4. Department of Biology , University of North Carolina Wilmington , Wilmington , NC , USA |
| Abstract: | Quantitative trait loci (QTL) mapping is a growing field in statistical genetics. In plants, QTL detection experiments often feature replicates or clones within a specific genetic line. In this work, a Bayesian hierarchical regression model is applied to simulated QTL data and to a dataset from the Arabidopsis thaliana plants for locating the QTL mapping associated with cotyledon opening. A conditional model search strategy based on Bayesian model averaging is utilized to reduce the computational burden. |
| Keywords: | hierarchical models Bayesian statistics quantitative trait loci Bayesian model averaging recombinant inbred Lines |