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Separation of base allele and sampling term effects gives new insights in variance component QTL analysis
BACKGROUND: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1781068/ https://www.ncbi.nlm.nih.gov/pubmed/17210073 http://dx.doi.org/10.1186/1471-2156-8-1 |
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author | Rönnegård, Lars Carlborg, Örjan |
author_facet | Rönnegård, Lars Carlborg, Örjan |
author_sort | Rönnegård, Lars |
collection | PubMed |
description | BACKGROUND: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix). RESULTS: We present an alternative notation of the variance component model, where the elements of the random effect are independent base generation allele effects and sampling term effects. The relationship between the phenotypic vales and the random effect is given by an incidence matrix, which results in a novel, but statistically equivalent, version of the traditional VC model. A general algorithm to estimate this incidence matrix is presented. Since the model is given in terms of base generation allele effects and sampling term effects, these effects can be estimated separately using best linear unbiased prediction (BLUP). From simulated data, we showed that biallelic QTL effects could be accurately clustered using the BLUP obtained from our model notation when markers are fully informative, and that the accuracy increased with the size of the QTL effect. We also developed a measure indicating whether a base generation marker homozygote is a QTL heterozygote or not, by comparing the variances of the sampling term BLUP and the base generation allele BLUP. A ratio greater than one gives strong support for a QTL heterozygote. CONCLUSION: We developed a simple presentation of the VC QTL model for identification of base generation allele effects in QTL linkage analysis. The base generation allele effects and sampling term effects were separated in our model notation. This clarifies the assumptions of the model and should also enhance the development of genome scan methods. |
format | Text |
id | pubmed-1781068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-17810682007-01-30 Separation of base allele and sampling term effects gives new insights in variance component QTL analysis Rönnegård, Lars Carlborg, Örjan BMC Genet Methodology Article BACKGROUND: Variance component (VC) models are commonly used for Quantitative Trait Loci (QTL) mapping in outbred populations. Here, the QTL effect is given as a random effect and a critical part of the model is the relationship between the phenotypic values and the random effect. In the traditional VC model, each individual has a unique QTL effect and the relationship between these random effects is given as a covariance structure (known as the identity-by-descent (IBD) matrix). RESULTS: We present an alternative notation of the variance component model, where the elements of the random effect are independent base generation allele effects and sampling term effects. The relationship between the phenotypic vales and the random effect is given by an incidence matrix, which results in a novel, but statistically equivalent, version of the traditional VC model. A general algorithm to estimate this incidence matrix is presented. Since the model is given in terms of base generation allele effects and sampling term effects, these effects can be estimated separately using best linear unbiased prediction (BLUP). From simulated data, we showed that biallelic QTL effects could be accurately clustered using the BLUP obtained from our model notation when markers are fully informative, and that the accuracy increased with the size of the QTL effect. We also developed a measure indicating whether a base generation marker homozygote is a QTL heterozygote or not, by comparing the variances of the sampling term BLUP and the base generation allele BLUP. A ratio greater than one gives strong support for a QTL heterozygote. CONCLUSION: We developed a simple presentation of the VC QTL model for identification of base generation allele effects in QTL linkage analysis. The base generation allele effects and sampling term effects were separated in our model notation. This clarifies the assumptions of the model and should also enhance the development of genome scan methods. BioMed Central 2007-01-08 /pmc/articles/PMC1781068/ /pubmed/17210073 http://dx.doi.org/10.1186/1471-2156-8-1 Text en Copyright © 2007 Rönnegård and Carlborg; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methodology Article Rönnegård, Lars Carlborg, Örjan Separation of base allele and sampling term effects gives new insights in variance component QTL analysis |
title | Separation of base allele and sampling term effects gives new insights in variance component QTL analysis |
title_full | Separation of base allele and sampling term effects gives new insights in variance component QTL analysis |
title_fullStr | Separation of base allele and sampling term effects gives new insights in variance component QTL analysis |
title_full_unstemmed | Separation of base allele and sampling term effects gives new insights in variance component QTL analysis |
title_short | Separation of base allele and sampling term effects gives new insights in variance component QTL analysis |
title_sort | separation of base allele and sampling term effects gives new insights in variance component qtl analysis |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1781068/ https://www.ncbi.nlm.nih.gov/pubmed/17210073 http://dx.doi.org/10.1186/1471-2156-8-1 |
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