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Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!

One of the most popular modeling approaches to genetic risk prediction is to use a summary of risk alleles in the form of an unweighted or a weighted genetic risk score, with weights that relate to the odds for the phenotype in carriers of the individual alleles. Recent contributions have proposed t...

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Detalles Bibliográficos
Autores principales: Sebastiani, Paola, Solovieff, Nadia, Sun, Jenny X.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3289795/
https://www.ncbi.nlm.nih.gov/pubmed/22393331
http://dx.doi.org/10.3389/fgene.2012.00026
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author Sebastiani, Paola
Solovieff, Nadia
Sun, Jenny X.
author_facet Sebastiani, Paola
Solovieff, Nadia
Sun, Jenny X.
author_sort Sebastiani, Paola
collection PubMed
description One of the most popular modeling approaches to genetic risk prediction is to use a summary of risk alleles in the form of an unweighted or a weighted genetic risk score, with weights that relate to the odds for the phenotype in carriers of the individual alleles. Recent contributions have proposed the use of Bayesian classification rules using Naïve Bayes classifiers. We examine the relation between the two approaches for genetic risk prediction and show that the methods are mathematically related. In addition, we study the properties of the two approaches and describe how they can be generalized to include various models of inheritance.
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spelling pubmed-32897952012-03-05 Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all! Sebastiani, Paola Solovieff, Nadia Sun, Jenny X. Front Genet Genetics One of the most popular modeling approaches to genetic risk prediction is to use a summary of risk alleles in the form of an unweighted or a weighted genetic risk score, with weights that relate to the odds for the phenotype in carriers of the individual alleles. Recent contributions have proposed the use of Bayesian classification rules using Naïve Bayes classifiers. We examine the relation between the two approaches for genetic risk prediction and show that the methods are mathematically related. In addition, we study the properties of the two approaches and describe how they can be generalized to include various models of inheritance. Frontiers Research Foundation 2012-02-29 /pmc/articles/PMC3289795/ /pubmed/22393331 http://dx.doi.org/10.3389/fgene.2012.00026 Text en Copyright © 2012 Sebastiani, Solovieff and Sun. https://creativecommons.org/licenses/by/3.0/This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
spellingShingle Genetics
Sebastiani, Paola
Solovieff, Nadia
Sun, Jenny X.
Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!
title Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!
title_full Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!
title_fullStr Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!
title_full_unstemmed Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!
title_short Naïve Bayesian Classifier and Genetic Risk Score for Genetic Risk Prediction of a Categorical Trait: Not so Different after all!
title_sort naïve bayesian classifier and genetic risk score for genetic risk prediction of a categorical trait: not so different after all!
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3289795/
https://www.ncbi.nlm.nih.gov/pubmed/22393331
http://dx.doi.org/10.3389/fgene.2012.00026
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