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MANTIS: an R package that simulates multilocus models of pathogen evolution

BACKGROUND: In host-pathogen systems the development of immunity by the host places pressure on pathogens, by setting up competition between genetic variants due to the establishment of cross-protective responses. These pressures can lead to pathogen-specific, ubiquitous dynamic behaviours. Understa...

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Detalles Bibliográficos
Autores principales: Lourenço, José, Wikramaratna, Paul S, Gupta, Sunetra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445977/
https://www.ncbi.nlm.nih.gov/pubmed/26017358
http://dx.doi.org/10.1186/s12859-015-0598-9
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author Lourenço, José
Wikramaratna, Paul S
Gupta, Sunetra
author_facet Lourenço, José
Wikramaratna, Paul S
Gupta, Sunetra
author_sort Lourenço, José
collection PubMed
description BACKGROUND: In host-pathogen systems the development of immunity by the host places pressure on pathogens, by setting up competition between genetic variants due to the establishment of cross-protective responses. These pressures can lead to pathogen-specific, ubiquitous dynamic behaviours. Understanding the evolutionary forces that shape these patterns is one of the key goals of computationally simulated epidemiological models. Despite the contribution of such research methods in recent years to our current understanding of pathogen evolution, the availability of free software tools for the general public remains scarce. RESULTS: We developed the Multilocus ANTIgenic Simulator (MANTIS) software package for the R statistical environment. MANTIS can simulate and analyse epidemiological time-series generated under the biological assumptions of the strain theory of host-pathogen systems by Gupta et al. CONCLUSIONS: MANTIS wraps a C/C++ ordinary-differential equations system and Runge-Kutta solver into a set of user-friendly R functions. These include routines to numerically simulate the system and others to analyse, visualize and export results. For this, the package offers its own set of time-series plotting and exportation functions. MANTIS’s main goal is to serve as a free, ready-to-use academic software tool. Its open source nature further provides an opportunity for users with advanced programming skills to expand its capabilities. Here, we describe the background theory, implementation, basic functionality and usage of this package. MANTIS is freely available from http://www.eeid.ox.ac.uk/mantisunder the GPL license. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0598-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-44459772015-05-28 MANTIS: an R package that simulates multilocus models of pathogen evolution Lourenço, José Wikramaratna, Paul S Gupta, Sunetra BMC Bioinformatics Software BACKGROUND: In host-pathogen systems the development of immunity by the host places pressure on pathogens, by setting up competition between genetic variants due to the establishment of cross-protective responses. These pressures can lead to pathogen-specific, ubiquitous dynamic behaviours. Understanding the evolutionary forces that shape these patterns is one of the key goals of computationally simulated epidemiological models. Despite the contribution of such research methods in recent years to our current understanding of pathogen evolution, the availability of free software tools for the general public remains scarce. RESULTS: We developed the Multilocus ANTIgenic Simulator (MANTIS) software package for the R statistical environment. MANTIS can simulate and analyse epidemiological time-series generated under the biological assumptions of the strain theory of host-pathogen systems by Gupta et al. CONCLUSIONS: MANTIS wraps a C/C++ ordinary-differential equations system and Runge-Kutta solver into a set of user-friendly R functions. These include routines to numerically simulate the system and others to analyse, visualize and export results. For this, the package offers its own set of time-series plotting and exportation functions. MANTIS’s main goal is to serve as a free, ready-to-use academic software tool. Its open source nature further provides an opportunity for users with advanced programming skills to expand its capabilities. Here, we describe the background theory, implementation, basic functionality and usage of this package. MANTIS is freely available from http://www.eeid.ox.ac.uk/mantisunder the GPL license. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0598-9) contains supplementary material, which is available to authorized users. BioMed Central 2015-05-28 /pmc/articles/PMC4445977/ /pubmed/26017358 http://dx.doi.org/10.1186/s12859-015-0598-9 Text en © Lourenço et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Lourenço, José
Wikramaratna, Paul S
Gupta, Sunetra
MANTIS: an R package that simulates multilocus models of pathogen evolution
title MANTIS: an R package that simulates multilocus models of pathogen evolution
title_full MANTIS: an R package that simulates multilocus models of pathogen evolution
title_fullStr MANTIS: an R package that simulates multilocus models of pathogen evolution
title_full_unstemmed MANTIS: an R package that simulates multilocus models of pathogen evolution
title_short MANTIS: an R package that simulates multilocus models of pathogen evolution
title_sort mantis: an r package that simulates multilocus models of pathogen evolution
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445977/
https://www.ncbi.nlm.nih.gov/pubmed/26017358
http://dx.doi.org/10.1186/s12859-015-0598-9
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