Estimating Effects and Variance Components in Models of Quantitative Genetics in an Era Sequenced Genomes

Charles Mode

Estimating Effects and Variance Components in Models of Quantitative Genetics in an Era of Sequenced Genomes

Charles J. Mode * §

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§ Drexel University

Estimating Effects and Variance Components in Models of Quantitative Genetics in an Era of Sequenced Genomes

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Abstract

As in many other areas of research in genetics, the availability of sequenced genomes in samples of individuals has revolutionized the study of quantitative traits, because researches have developed statistical evidence regarding the lo- cations of genomic regions, loci, that have been implicated with the expression of a quantitative trait or traits. Therefore, in cases in which it is possible to develop operational definitions of at least two alleles at each locus, genomic regions, it becomes possible to identify the genotype of each individual with re- spect to a set of loci that have been shown in other experiments to influence the expression of a quantitative trait. As will be shown in this paper, by knowing the genotype of each individual in a sample with respect to a set of identified loci, it is now possible to directly estimate eﬀects that are measures of not only intra-allelic interactions at each locus under consideration but also various types of epistatic eﬀects that are measures of interactions among alleles at diﬀerent loci, governing the inheritance of a quantitative trait. These straight forward methods of estimation diﬀer from those used in classical quantitative genetics, because such eﬀects and corresponding variance components could be estimated indirectly, using analysis of variance procedures or some version of general lin- ear models that have been and are widely in statistical genetics. The direct method of estimation described in this paper, show promise towards shifting the working paradigm that has been used in classical models of the genetics of quantitative traits involving the estimation of variance components to a more direct approach and simpler approach.

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3 Cites in Article

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1. Yoav Benjamini,Yosef Hochberg (1995). Controlling false discovery rate: A practical and powerful approach to multiple testing. J. Roy. Soc. Ser. B, 57(1), 289-300.
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2. Yoav Benjamini,Daniel Yekutieli (2001). The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics, 29(4), 1165-1188.
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3. Y. Benjamini,D. Yekutieli (2005). False Discovery Rate–Adjusted Multiple Confidence Intervals for Selected Parameters.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Charles J. Mode. 2014. "Estimating Effects and Variance Components in Models of Quantitative Genetics in an Era of Sequenced Genomes". Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 14 (GJSFR Volume 14 Issue 31 (F5)).

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GJSFR Volume 14 Issue 31 (F5)

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Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

direct estimates of effects effects as measures of intra-allelic and epistatic interactions genetic and environmental variance components genomic regions implicated with a quantitative trait intra-allelic interaction and epistatic components of variance known genotypes loci locus and alleles partitioning the genetic variance into additive Phenotypic

Classification

GJSFR-F Classification MSC 2010: 97K80

Submission ReceivedJuly 10, 2014
Peer Review Double Blind
Handling Editor
Accepted July 30, 2014
Published August 11, 2014

Version of record

v1.2

Issue date

August 11, 2014

Language

English

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Article Matrices

Total Score: 131

Country: United States

Subject: Global Journal of Science Frontier Research - F: Mathematics & Decision

Authors: Charles J. Mode (PhD/Dr. count: 0)

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