Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.

The problem of genotyping polyploids is extremely important for the creation of genetic maps and assembly of complex plant genomes. Despite its significance, polyploid genotyping still remains largely unsolved and suffers from a lack of statistical formality. In this paper a graphical bayesian model...

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Autores principales:	Oliver Serang, Marcelo Mollinari, Antonio Augusto Franco Garcia
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bb088c36991549d9bc7a3c377643ed33
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id	oai:doaj.org-article:bb088c36991549d9bc7a3c377643ed33
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spelling	oai:doaj.org-article:bb088c36991549d9bc7a3c377643ed332021-11-18T07:27:42ZEfficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.1932-620310.1371/journal.pone.0030906https://doaj.org/article/bb088c36991549d9bc7a3c377643ed332012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22363513/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203The problem of genotyping polyploids is extremely important for the creation of genetic maps and assembly of complex plant genomes. Despite its significance, polyploid genotyping still remains largely unsolved and suffers from a lack of statistical formality. In this paper a graphical bayesian model for SNP genotyping data is introduced. This model can infer genotypes even when the ploidy of the population is unknown. We also introduce an algorithm for finding the exact maximum a posteriori genotype configuration with this model. This algorithm is implemented in a freely available web-based software package SuperMASSA. We demonstrate the utility, efficiency, and flexibility of the model and algorithm by applying them to two different platforms, each of which is applied to a polyploid data set: Illumina GoldenGate data from potato and Sequenom MassARRAY data from sugarcane. Our method achieves state-of-the-art performance on both data sets and can be trivially adapted to use models that utilize prior information about any platform or species.Oliver SerangMarcelo MollinariAntonio Augusto Franco GarciaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 2, p e30906 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Oliver Serang Marcelo Mollinari Antonio Augusto Franco Garcia Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.
description	The problem of genotyping polyploids is extremely important for the creation of genetic maps and assembly of complex plant genomes. Despite its significance, polyploid genotyping still remains largely unsolved and suffers from a lack of statistical formality. In this paper a graphical bayesian model for SNP genotyping data is introduced. This model can infer genotypes even when the ploidy of the population is unknown. We also introduce an algorithm for finding the exact maximum a posteriori genotype configuration with this model. This algorithm is implemented in a freely available web-based software package SuperMASSA. We demonstrate the utility, efficiency, and flexibility of the model and algorithm by applying them to two different platforms, each of which is applied to a polyploid data set: Illumina GoldenGate data from potato and Sequenom MassARRAY data from sugarcane. Our method achieves state-of-the-art performance on both data sets and can be trivially adapted to use models that utilize prior information about any platform or species.
format	article
author	Oliver Serang Marcelo Mollinari Antonio Augusto Franco Garcia
author_facet	Oliver Serang Marcelo Mollinari Antonio Augusto Franco Garcia
author_sort	Oliver Serang
title	Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.
title_short	Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.
title_full	Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.
title_fullStr	Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.
title_full_unstemmed	Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.
title_sort	efficient exact maximum a posteriori computation for bayesian snp genotyping in polyploids.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/bb088c36991549d9bc7a3c377643ed33
work_keys_str_mv	AT oliverserang efficientexactmaximumaposterioricomputationforbayesiansnpgenotypinginpolyploids AT marcelomollinari efficientexactmaximumaposterioricomputationforbayesiansnpgenotypinginpolyploids AT antonioaugustofrancogarcia efficientexactmaximumaposterioricomputationforbayesiansnpgenotypinginpolyploids
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Efficient exact maximum a posteriori computation for bayesian SNP genotyping in polyploids.

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