Adjusting for Covariates in Variance Components QTL Linkage Analysis.
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| Title: | Adjusting for Covariates in Variance Components QTL Linkage Analysis. |
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| Authors: | Zeegers, Maurice, Rijsdijk, Fruhling, Sham, Pak |
| Source: | Behavior Genetics. Mar2004, Vol. 34 Issue 2, p127-133. 7p. |
| Subjects: | Linkage (Genetics), Genetics, Locus (Genetics), Variate difference method, Analysis of covariance |
| Abstract: | Variance components modeling has emerged as a powerful method for quantitative trait loci (QTL) linkage analysis. However, the power to detect a gene of minor effect is low. Many complex traits are affected by environmental as well as genetic factors, and one strategy to increase power is to reduce nongenetic phenotypic variance by adjusting for environmental covariates. In this paper, we investigate the power of three approaches to covariate adjustment in variance components linkage analysis: (i) incorporate covariates in the means model, (ii) incorporate covariates in the covariance matrix, and (iii) perform analysis on residual statistics. These approaches are compared to an analysis without adjustment. The results show that in the absence of correlation between the covariate and the QTL effect, adjusting for covariates indeed increases power to detect an underlying QTL. As this correlation increases, however, the power decreases. In the presence of a causal association between QTL and covariates, not adjusting for covariates appeared to be more powerful. The three approaches for adjusting for covariate: residual statistics, the means model, and the covariance model, had equal power to detect a QTL. [ABSTRACT FROM AUTHOR] |
| Copyright of Behavior Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 12108408 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Adjusting for Covariates in Variance Components QTL Linkage Analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zeegers%2C+Maurice%22">Zeegers, Maurice</searchLink><br /><searchLink fieldCode="AR" term="%22Rijsdijk%2C+Fruhling%22">Rijsdijk, Fruhling</searchLink><br /><searchLink fieldCode="AR" term="%22Sham%2C+Pak%22">Sham, Pak</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Behavior+Genetics%22">Behavior Genetics</searchLink>. Mar2004, Vol. 34 Issue 2, p127-133. 7p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Linkage+%28Genetics%29%22">Linkage (Genetics)</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Locus+%28Genetics%29%22">Locus (Genetics)</searchLink><br /><searchLink fieldCode="DE" term="%22Variate+difference+method%22">Variate difference method</searchLink><br /><searchLink fieldCode="DE" term="%22Analysis+of+covariance%22">Analysis of covariance</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Variance components modeling has emerged as a powerful method for quantitative trait loci (QTL) linkage analysis. However, the power to detect a gene of minor effect is low. Many complex traits are affected by environmental as well as genetic factors, and one strategy to increase power is to reduce nongenetic phenotypic variance by adjusting for environmental covariates. In this paper, we investigate the power of three approaches to covariate adjustment in variance components linkage analysis: (i) incorporate covariates in the means model, (ii) incorporate covariates in the covariance matrix, and (iii) perform analysis on residual statistics. These approaches are compared to an analysis without adjustment. The results show that in the absence of correlation between the covariate and the QTL effect, adjusting for covariates indeed increases power to detect an underlying QTL. As this correlation increases, however, the power decreases. In the presence of a causal association between QTL and covariates, not adjusting for covariates appeared to be more powerful. The three approaches for adjusting for covariate: residual statistics, the means model, and the covariance model, had equal power to detect a QTL. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Behavior Genetics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1023/B:BEGE.0000013726.65708.c2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 127 Subjects: – SubjectFull: Linkage (Genetics) Type: general – SubjectFull: Genetics Type: general – SubjectFull: Locus (Genetics) Type: general – SubjectFull: Variate difference method Type: general – SubjectFull: Analysis of covariance Type: general Titles: – TitleFull: Adjusting for Covariates in Variance Components QTL Linkage Analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zeegers, Maurice – PersonEntity: Name: NameFull: Rijsdijk, Fruhling – PersonEntity: Name: NameFull: Sham, Pak IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2004 Type: published Y: 2004 Identifiers: – Type: issn-print Value: 00018244 Numbering: – Type: volume Value: 34 – Type: issue Value: 2 Titles: – TitleFull: Behavior Genetics Type: main |
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