title: Extended Bayesian LASSO for multiple quantitative trait loci mapping and unobserved phenotype prediction.
abstract: The Bayesian LASSO (BL) has been pointed out to be an effective approach to sparse model representation and successfully applied to quantitative trait loci (QTL) mapping and genomic breeding value (GBV) estimation using genome-wide dense sets of markers. However, the BL relies on a single parameter known as the regularization parameter to simultaneously control the overall model sparsity and the shrinkage of individual covariate effects. This may be idealistic when dealing with a large number of predictors whose effect sizes may differ by orders of magnitude. Here we propose the extended Bayesian LASSO (EBL) for QTL mapping and unobserved phenotype prediction, which introduces an additional level to the hierarchical specification of the BL to explicitly separate out these two model features. Compared to the adaptiveness of the BL, the EBL is "doubly adaptive" and thus, more robust to tuning. In simulations, the EBL outperformed the BL in regard to the accuracy of both effect size estimates and phenotypic value predictions, with comparable computational time. Moreover, the EBL proved to be less sensitive to tuning than the related Bayesian adaptive LASSO (BAL), which introduces locus-specific regularization parameters as well, but involves no mechanism for distinguishing between model sparsity and parameter shrinkage. Consequently, the EBL seems to point to a new direction for QTL mapping, phenotype prediction, and GBV estimation.
authors.affiliation: Department of Agricultural Sciences, University of Helsinki, Helsinki FIN-00014, Finland.
authors.forename: Crispin M
authors.initials: CM
authors.lastname: Mutshinda
authors.forename: Mikko J
authors.initials: MJ
authors.lastname: Sillanpää
mesh_terms: D001499:Bayes Theorem; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D030541:Databases, Genetic; D005819:Genetic Markers; D001467:Hordeum / Q000235:genetics; D008957:Models, Genetic; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics*; D015203:Reproducibility of Results
chemical_list: D005819:Genetic Markers
references.citation: PLoS Genet. 2007 Jul;3(7):e114
references.pmid: 17676998
references.citation: Genet Res (Camb). 2009 Dec;91(6):427-36
references.pmid: 20122298
references.citation: Genetics. 2001 Sep;159(1):371-87
references.pmid: 11560912
references.citation: Genet Res. 2000 Apr;75(2):249-52
references.pmid: 10816982
references.citation: PLoS Genet. 2008 Oct;4(10):e1000231
references.pmid: 18949033
references.citation: Genetics. 2010 May;185(1):349-59
references.pmid: 20157003
references.citation: Heredity (Edinb). 2005 Jul;95(1):96-104
references.pmid: 15931238
references.citation: Genetics. 2009 May;182(1):375-85
references.pmid: 19293140
references.citation: Genetics. 2005 May;170(1):465-80
references.pmid: 15781696
references.citation: Genetics. 2007 Apr;175(4):1955-63
references.pmid: 17277367
references.citation: Bioinformatics. 2009 Mar 15;25(6):714-21
references.pmid: 19176549
references.citation: Genetics. 2003 Feb;163(2):789-801
references.pmid: 12618414
references.citation: Genet Res (Camb). 2009 Feb;91(1):23-37
references.pmid: 19220929
references.citation: Am J Hum Genet. 2008 Feb;82(2):375-85
references.pmid: 18252218
references.citation: Heredity (Edinb). 2009 Sep;103(3):223-37
references.pmid: 19455182
references.citation: Genetics. 2008 Jun;179(2):1045-55
references.pmid: 18505874
references.citation: Biometrics. 2007 Jun;63(2):513-21
references.pmid: 17688503
references.citation: Heredity (Edinb). 2008 Sep;101(3):271-84
references.pmid: 18648392
references.citation: Genetics. 1994 Nov;138(3):963-71
references.pmid: 7851788