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Uncovering the Genetic Architectures of Quantitative Traits
The aim of a genome-wide association study (GWAS) is to identify loci in the human genome affecting a phenotype of interest. This review summarizes some recent work on conceptual and methodological aspects of GWAS. The average effect of gene substitution at a given causal site in the genome is the k...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816193/ https://www.ncbi.nlm.nih.gov/pubmed/27076877 http://dx.doi.org/10.1016/j.csbj.2015.10.002 |
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author | Lee, James J. Vattikuti, Shashaank Chow, Carson C. |
author_facet | Lee, James J. Vattikuti, Shashaank Chow, Carson C. |
author_sort | Lee, James J. |
collection | PubMed |
description | The aim of a genome-wide association study (GWAS) is to identify loci in the human genome affecting a phenotype of interest. This review summarizes some recent work on conceptual and methodological aspects of GWAS. The average effect of gene substitution at a given causal site in the genome is the key estimand in GWAS, and we argue for its fundamental importance. Implicit in the definition of average effect is a linear model relating genotype to phenotype. The fraction of the phenotypic variance ascribable to polymorphic sites with nonzero average effects in this linear model is called the heritability, and we describe methods for estimating this quantity from GWAS data. Finally, we show that the theory of compressed sensing can be used to provide a sharp estimate of the sample size required to identify essentially all sites contributing to the heritability of a given phenotype. |
format | Online Article Text |
id | pubmed-4816193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-48161932016-04-13 Uncovering the Genetic Architectures of Quantitative Traits Lee, James J. Vattikuti, Shashaank Chow, Carson C. Comput Struct Biotechnol J Mini Review The aim of a genome-wide association study (GWAS) is to identify loci in the human genome affecting a phenotype of interest. This review summarizes some recent work on conceptual and methodological aspects of GWAS. The average effect of gene substitution at a given causal site in the genome is the key estimand in GWAS, and we argue for its fundamental importance. Implicit in the definition of average effect is a linear model relating genotype to phenotype. The fraction of the phenotypic variance ascribable to polymorphic sites with nonzero average effects in this linear model is called the heritability, and we describe methods for estimating this quantity from GWAS data. Finally, we show that the theory of compressed sensing can be used to provide a sharp estimate of the sample size required to identify essentially all sites contributing to the heritability of a given phenotype. Research Network of Computational and Structural Biotechnology 2015-11-23 /pmc/articles/PMC4816193/ /pubmed/27076877 http://dx.doi.org/10.1016/j.csbj.2015.10.002 Text en http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Mini Review Lee, James J. Vattikuti, Shashaank Chow, Carson C. Uncovering the Genetic Architectures of Quantitative Traits |
title | Uncovering the Genetic Architectures of Quantitative Traits |
title_full | Uncovering the Genetic Architectures of Quantitative Traits |
title_fullStr | Uncovering the Genetic Architectures of Quantitative Traits |
title_full_unstemmed | Uncovering the Genetic Architectures of Quantitative Traits |
title_short | Uncovering the Genetic Architectures of Quantitative Traits |
title_sort | uncovering the genetic architectures of quantitative traits |
topic | Mini Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4816193/ https://www.ncbi.nlm.nih.gov/pubmed/27076877 http://dx.doi.org/10.1016/j.csbj.2015.10.002 |
work_keys_str_mv | AT leejamesj uncoveringthegeneticarchitecturesofquantitativetraits AT vattikutishashaank uncoveringthegeneticarchitecturesofquantitativetraits AT chowcarsonc uncoveringthegeneticarchitecturesofquantitativetraits |