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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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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