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Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood

The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from...

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Detalles Bibliográficos
Autores principales: Uh, Hae-Won, Eilers, Paul H. C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3169573/
https://www.ncbi.nlm.nih.gov/pubmed/21931662
http://dx.doi.org/10.1371/journal.pone.0024219
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author Uh, Hae-Won
Eilers, Paul H. C.
author_facet Uh, Hae-Won
Eilers, Paul H. C.
author_sort Uh, Hae-Won
collection PubMed
description The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain (“fuzzy”) genotypes, like those resulting from AFLP scores, can be handled by adding an extra layer to the model. We describe the model and the estimation algorithm. We apply it to a data set of accurate human single nucleotide polymorphism (SNP) and to a data set of fuzzy tomato AFLP scores.
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spelling pubmed-31695732011-09-19 Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood Uh, Hae-Won Eilers, Paul H. C. PLoS One Research Article The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain (“fuzzy”) genotypes, like those resulting from AFLP scores, can be handled by adding an extra layer to the model. We describe the model and the estimation algorithm. We apply it to a data set of accurate human single nucleotide polymorphism (SNP) and to a data set of fuzzy tomato AFLP scores. Public Library of Science 2011-09-08 /pmc/articles/PMC3169573/ /pubmed/21931662 http://dx.doi.org/10.1371/journal.pone.0024219 Text en Uh and Eilers. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Uh, Hae-Won
Eilers, Paul H. C.
Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood
title Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood
title_full Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood
title_fullStr Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood
title_full_unstemmed Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood
title_short Haplotype Estimation from Fuzzy Genotypes Using Penalized Likelihood
title_sort haplotype estimation from fuzzy genotypes using penalized likelihood
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3169573/
https://www.ncbi.nlm.nih.gov/pubmed/21931662
http://dx.doi.org/10.1371/journal.pone.0024219
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