Cargando…

Bayesian coestimation of phylogeny and sequence alignment

BACKGROUND: Two central problems in computational biology are the determination of the alignment and phylogeny of a set of biological sequences. The traditional approach to this problem is to first build a multiple alignment of these sequences, followed by a phylogenetic reconstruction step based on...

Descripción completa

Detalles Bibliográficos
Autores principales: Lunter, Gerton, Miklós, István, Drummond, Alexei, Jensen, Jens Ledet, Hein, Jotun
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1087833/
https://www.ncbi.nlm.nih.gov/pubmed/15804354
http://dx.doi.org/10.1186/1471-2105-6-83
_version_ 1782123825304961024
author Lunter, Gerton
Miklós, István
Drummond, Alexei
Jensen, Jens Ledet
Hein, Jotun
author_facet Lunter, Gerton
Miklós, István
Drummond, Alexei
Jensen, Jens Ledet
Hein, Jotun
author_sort Lunter, Gerton
collection PubMed
description BACKGROUND: Two central problems in computational biology are the determination of the alignment and phylogeny of a set of biological sequences. The traditional approach to this problem is to first build a multiple alignment of these sequences, followed by a phylogenetic reconstruction step based on this multiple alignment. However, alignment and phylogenetic inference are fundamentally interdependent, and ignoring this fact leads to biased and overconfident estimations. Whether the main interest be in sequence alignment or phylogeny, a major goal of computational biology is the co-estimation of both. RESULTS: We developed a fully Bayesian Markov chain Monte Carlo method for coestimating phylogeny and sequence alignment, under the Thorne-Kishino-Felsenstein model of substitution and single nucleotide insertion-deletion (indel) events. In our earlier work, we introduced a novel and efficient algorithm, termed the "indel peeling algorithm", which includes indels as phylogenetically informative evolutionary events, and resembles Felsenstein's peeling algorithm for substitutions on a phylogenetic tree. For a fixed alignment, our extension analytically integrates out both substitution and indel events within a proper statistical model, without the need for data augmentation at internal tree nodes, allowing for efficient sampling of tree topologies and edge lengths. To additionally sample multiple alignments, we here introduce an efficient partial Metropolized independence sampler for alignments, and combine these two algorithms into a fully Bayesian co-estimation procedure for the alignment and phylogeny problem. Our approach results in estimates for the posterior distribution of evolutionary rate parameters, for the maximum a-posteriori (MAP) phylogenetic tree, and for the posterior decoding alignment. Estimates for the evolutionary tree and multiple alignment are augmented with confidence estimates for each node height and alignment column. Our results indicate that the patterns in reliability broadly correspond to structural features of the proteins, and thus provides biologically meaningful information which is not existent in the usual point-estimate of the alignment. Our methods can handle input data of moderate size (10–20 protein sequences, each 100–200 bp), which we analyzed overnight on a standard 2 GHz personal computer. CONCLUSION: Joint analysis of multiple sequence alignment, evolutionary trees and additional evolutionary parameters can be now done within a single coherent statistical framework.
format Text
id pubmed-1087833
institution National Center for Biotechnology Information
language English
publishDate 2005
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-10878332005-04-30 Bayesian coestimation of phylogeny and sequence alignment Lunter, Gerton Miklós, István Drummond, Alexei Jensen, Jens Ledet Hein, Jotun BMC Bioinformatics Methodology Article BACKGROUND: Two central problems in computational biology are the determination of the alignment and phylogeny of a set of biological sequences. The traditional approach to this problem is to first build a multiple alignment of these sequences, followed by a phylogenetic reconstruction step based on this multiple alignment. However, alignment and phylogenetic inference are fundamentally interdependent, and ignoring this fact leads to biased and overconfident estimations. Whether the main interest be in sequence alignment or phylogeny, a major goal of computational biology is the co-estimation of both. RESULTS: We developed a fully Bayesian Markov chain Monte Carlo method for coestimating phylogeny and sequence alignment, under the Thorne-Kishino-Felsenstein model of substitution and single nucleotide insertion-deletion (indel) events. In our earlier work, we introduced a novel and efficient algorithm, termed the "indel peeling algorithm", which includes indels as phylogenetically informative evolutionary events, and resembles Felsenstein's peeling algorithm for substitutions on a phylogenetic tree. For a fixed alignment, our extension analytically integrates out both substitution and indel events within a proper statistical model, without the need for data augmentation at internal tree nodes, allowing for efficient sampling of tree topologies and edge lengths. To additionally sample multiple alignments, we here introduce an efficient partial Metropolized independence sampler for alignments, and combine these two algorithms into a fully Bayesian co-estimation procedure for the alignment and phylogeny problem. Our approach results in estimates for the posterior distribution of evolutionary rate parameters, for the maximum a-posteriori (MAP) phylogenetic tree, and for the posterior decoding alignment. Estimates for the evolutionary tree and multiple alignment are augmented with confidence estimates for each node height and alignment column. Our results indicate that the patterns in reliability broadly correspond to structural features of the proteins, and thus provides biologically meaningful information which is not existent in the usual point-estimate of the alignment. Our methods can handle input data of moderate size (10–20 protein sequences, each 100–200 bp), which we analyzed overnight on a standard 2 GHz personal computer. CONCLUSION: Joint analysis of multiple sequence alignment, evolutionary trees and additional evolutionary parameters can be now done within a single coherent statistical framework. BioMed Central 2005-04-01 /pmc/articles/PMC1087833/ /pubmed/15804354 http://dx.doi.org/10.1186/1471-2105-6-83 Text en Copyright © 2005 Lunter et al; licensee BioMed Central Ltd.
spellingShingle Methodology Article
Lunter, Gerton
Miklós, István
Drummond, Alexei
Jensen, Jens Ledet
Hein, Jotun
Bayesian coestimation of phylogeny and sequence alignment
title Bayesian coestimation of phylogeny and sequence alignment
title_full Bayesian coestimation of phylogeny and sequence alignment
title_fullStr Bayesian coestimation of phylogeny and sequence alignment
title_full_unstemmed Bayesian coestimation of phylogeny and sequence alignment
title_short Bayesian coestimation of phylogeny and sequence alignment
title_sort bayesian coestimation of phylogeny and sequence alignment
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1087833/
https://www.ncbi.nlm.nih.gov/pubmed/15804354
http://dx.doi.org/10.1186/1471-2105-6-83
work_keys_str_mv AT luntergerton bayesiancoestimationofphylogenyandsequencealignment
AT miklosistvan bayesiancoestimationofphylogenyandsequencealignment
AT drummondalexei bayesiancoestimationofphylogenyandsequencealignment
AT jensenjensledet bayesiancoestimationofphylogenyandsequencealignment
AT heinjotun bayesiancoestimationofphylogenyandsequencealignment