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This article is part of the supplement: Proceedings of the 14th European workshop on QTL mapping and marker assisted selection (QTL-MAS)

Open Access Proceedings

A Bayesian approach to detect QTL affecting a simulated binary and quantitative trait

Aniek C Bouwman1*, Luc LG Janss2 and Henri CM Heuven3

Author Affiliations

1 Animal Breeding and Genomics Centre, Wageningen University, P.O. Box 338, 6700AH Wageningen, The Netherlands

2 Aarhus University, DJF Department of Genetics and Biotechnology, P.O. Box 50, 8830 Tjele, Denmark

3 Clinical Sciences of Companion Animals, Faculty of Veterinary Medicine, Utrecht University, P.O. box 80163, 3508 TD Utrecht, The Netherlands

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BMC Proceedings 2011, 5(Suppl 3):S4  doi:10.1186/1753-6561-5-S3-S4

Published: 27 May 2011

Abstract

Background

We analyzed simulated data from the 14th QTL-MAS workshop using a Bayesian approach implemented in the program iBay. The data contained individuals genotypes for 10,031 SNPs and phenotyped for a quantitative and a binary trait.

Results

For the quantitative trait we mapped 8 out of 30 additive QTL, 1 out of 3 imprinted QTL and both epistatic pairs of QTL successfully. For the binary trait we mapped 11 out of 22 additive QTL successfully. Four out of 22 pleiotropic QTL were detected as such.

Conclusions

The Bayesian variable selection method showed to be a successful method for genome-wide association. This method was reasonably fast using dense marker maps.