PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment

<p>Abstract</p> <p>Background</p> <p>The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more re...

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Main Authors: Massingham Tim, Sipos Botond, Jordan Gregory E, Goldman Nick
Format: Article
Language:English
Published: BMC 2011-04-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/12/104
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spelling doaj-10131c55683d42e2a5fc2401faf54f1b2020-11-24T22:16:08ZengBMCBMC Bioinformatics1471-21052011-04-0112110410.1186/1471-2105-12-104PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environmentMassingham TimSipos BotondJordan Gregory EGoldman Nick<p>Abstract</p> <p>Background</p> <p>The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.</p> <p>Results</p> <p><monospace>PhyloSim</monospace> is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, <monospace>PhyloSim</monospace> can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing <monospace>PhyloSim</monospace> to be adapted to specific needs.</p> <p>Conclusions</p> <p>Close integration with <monospace>R</monospace> and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that <monospace>PhyloSim</monospace> will be useful to future studies involving simulated alignments.</p> http://www.biomedcentral.com/1471-2105/12/104
collection DOAJ
language English
format Article
sources DOAJ
author Massingham Tim
Sipos Botond
Jordan Gregory E
Goldman Nick
spellingShingle Massingham Tim
Sipos Botond
Jordan Gregory E
Goldman Nick
PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
BMC Bioinformatics
author_facet Massingham Tim
Sipos Botond
Jordan Gregory E
Goldman Nick
author_sort Massingham Tim
title PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
title_short PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
title_full PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
title_fullStr PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
title_full_unstemmed PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment
title_sort phylosim - monte carlo simulation of sequence evolution in the r statistical computing environment
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2011-04-01
description <p>Abstract</p> <p>Background</p> <p>The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.</p> <p>Results</p> <p><monospace>PhyloSim</monospace> is an extensible framework for the Monte Carlo simulation of sequence evolution, written in R, using the Gillespie algorithm to integrate the actions of many concurrent processes such as substitutions, insertions and deletions. Uniquely among sequence simulation tools, <monospace>PhyloSim</monospace> can simulate arbitrarily complex patterns of rate variation and multiple indel processes, and allows for the incorporation of selective constraints on indel events. User-defined complex patterns of mutation and selection can be easily integrated into simulations, allowing <monospace>PhyloSim</monospace> to be adapted to specific needs.</p> <p>Conclusions</p> <p>Close integration with <monospace>R</monospace> and the wide range of features implemented offer unmatched flexibility, making it possible to simulate sequence evolution under a wide range of realistic settings. We believe that <monospace>PhyloSim</monospace> will be useful to future studies involving simulated alignments.</p>
url http://www.biomedcentral.com/1471-2105/12/104
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