A revised Fisher model on analysis of quantitative trait loci with multiple alleles

Zeng et al. (2005) proposed a general two-allele (G2A) model to model bi-allelic quantitative trait loci (QTL). Comparing with the classical Fisher model, the G2A model can avoid using redundant parameters and be fitted directly using standard least square (LS) approach. In this study, we further e...

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Main Author: Tao eWang
Format: Article
Language:English
Published: Frontiers Media S.A. 2014-09-01
Series:Frontiers in Genetics
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fgene.2014.00328/full
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spelling doaj-3392ab473b954804a472d1c976a62e842020-11-24T23:13:56ZengFrontiers Media S.A.Frontiers in Genetics1664-80212014-09-01510.3389/fgene.2014.00328109610A revised Fisher model on analysis of quantitative trait loci with multiple allelesTao eWang0Medical College of WisconsinZeng et al. (2005) proposed a general two-allele (G2A) model to model bi-allelic quantitative trait loci (QTL). Comparing with the classical Fisher model, the G2A model can avoid using redundant parameters and be fitted directly using standard least square (LS) approach. In this study, we further extend the G2A model to general multi-allele (GMA) model. First, we propose a one-locus GMA model for phase known genotypes based on modeling the inheritance of paternal and maternal alleles. Next, we develop a one-locus GMA model for phase unknown genotypes by treating it as a special case of the phase known one-locus GMA model. Thirdly, we extend the one-locus GMA models to multiple loci. We discuss how the genetic variance components can be analyzed using these GMA models in equilibrium as well as disequilibrium populations. Finally, we apply the GMA model to a published experimental data set.http://journal.frontiersin.org/Journal/10.3389/fgene.2014.00328/fullorthogonalityFisher's genetic modelgenetic variance componentsgeneral two-allele modelgeneral multi-allele modelleast square approach
collection DOAJ
language English
format Article
sources DOAJ
author Tao eWang
spellingShingle Tao eWang
A revised Fisher model on analysis of quantitative trait loci with multiple alleles
Frontiers in Genetics
orthogonality
Fisher's genetic model
genetic variance components
general two-allele model
general multi-allele model
least square approach
author_facet Tao eWang
author_sort Tao eWang
title A revised Fisher model on analysis of quantitative trait loci with multiple alleles
title_short A revised Fisher model on analysis of quantitative trait loci with multiple alleles
title_full A revised Fisher model on analysis of quantitative trait loci with multiple alleles
title_fullStr A revised Fisher model on analysis of quantitative trait loci with multiple alleles
title_full_unstemmed A revised Fisher model on analysis of quantitative trait loci with multiple alleles
title_sort revised fisher model on analysis of quantitative trait loci with multiple alleles
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2014-09-01
description Zeng et al. (2005) proposed a general two-allele (G2A) model to model bi-allelic quantitative trait loci (QTL). Comparing with the classical Fisher model, the G2A model can avoid using redundant parameters and be fitted directly using standard least square (LS) approach. In this study, we further extend the G2A model to general multi-allele (GMA) model. First, we propose a one-locus GMA model for phase known genotypes based on modeling the inheritance of paternal and maternal alleles. Next, we develop a one-locus GMA model for phase unknown genotypes by treating it as a special case of the phase known one-locus GMA model. Thirdly, we extend the one-locus GMA models to multiple loci. We discuss how the genetic variance components can be analyzed using these GMA models in equilibrium as well as disequilibrium populations. Finally, we apply the GMA model to a published experimental data set.
topic orthogonality
Fisher's genetic model
genetic variance components
general two-allele model
general multi-allele model
least square approach
url http://journal.frontiersin.org/Journal/10.3389/fgene.2014.00328/full
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