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

A.C. Bouwman, L.L.G. Janss, H.C.M. Heuven

Research output: Contribution to journalArticleAcademicpeer-review

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
Original languageEnglish
Article numberS4
Number of pages6
JournalBMC Proceedings
Volume5
Issue numberSuppl. 3
DOIs
Publication statusPublished - 2011

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Bayes Theorem
Genes
Single Nucleotide Polymorphism
Genotype
Genome
Education

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A Bayesian approach to detect QTL affecting a simulated binary and quatitative trait. / Bouwman, A.C.; Janss, L.L.G.; Heuven, H.C.M.

In: BMC Proceedings, Vol. 5, No. Suppl. 3, S4, 2011.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - A Bayesian approach to detect QTL affecting a simulated binary and quatitative trait

AU - Bouwman, A.C.

AU - Janss, L.L.G.

AU - Heuven, H.C.M.

PY - 2011

Y1 - 2011

N2 - 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

AB - 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

U2 - 10.1186/1753-6561-5-S3-S4

DO - 10.1186/1753-6561-5-S3-S4

M3 - Article

VL - 5

JO - BMC Proceedings

JF - BMC Proceedings

SN - 1753-6561

IS - Suppl. 3

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