MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics.

Raphaël Helaers, Michel C Milinkovitch
Author Information
  1. Raphaël Helaers: Department of Biology of Namur University, Belgium.

Abstract

BACKGROUND: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities.
RESULTS: Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers.
CONCLUSIONS: The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at http://www.metapiga.org.

References

  1. Trends Ecol Evol. 2004 Aug;19(8):430-8 [PMID: 16701301]
  2. Syst Biol. 2006 Aug;55(4):579-94 [PMID: 16857652]
  3. J Mol Evol. 1981;17(6):368-76 [PMID: 7288891]
  4. Syst Biol. 2002 Oct;51(5):673-88 [PMID: 12396583]
  5. Science. 1983 May 13;220(4598):671-80 [PMID: 17813860]
  6. Mol Biol Evol. 2002 Sep;19(9):1483-9 [PMID: 12200476]
  7. Mol Biol Evol. 1987 Jul;4(4):406-25 [PMID: 3447015]
  8. Proc Natl Acad Sci U S A. 2000 Oct 10;97(21):11343-7 [PMID: 11027333]
  9. Syst Biol. 2001 Feb;50(1):7-17 [PMID: 12116596]
  10. Syst Biol. 2001 Aug;50(4):580-601 [PMID: 12116655]
  11. Mol Biol Evol. 1998 Dec;15(12):1647-57 [PMID: 9866200]
  12. Science. 2002 Oct 11;298(5592):379 [PMID: 12376694]
  13. Nat Rev Genet. 2003 Apr;4(4):275-84 [PMID: 12671658]
  14. Methods Enzymol. 2005;395:652-70 [PMID: 15865989]
  15. Mol Biol Evol. 1995 Jul;12(4):546-57 [PMID: 7659011]
  16. Mol Biol Evol. 1998 Mar;15(3):277-83 [PMID: 9501494]
  17. Bioinformatics. 2009 Jun 1;25(11):1370-6 [PMID: 19369496]
  18. J Mol Evol. 1994 Sep;39(3):306-14 [PMID: 7932792]
  19. Syst Biol. 2002 Oct;51(5):689-702 [PMID: 12396584]
  20. Pac Symp Biocomput. 1996;:512-23 [PMID: 9390255]
  21. Proc Natl Acad Sci U S A. 2002 Aug 6;99(16):10516-21 [PMID: 12142465]
  22. Syst Biol. 2003 Oct;52(5):696-704 [PMID: 14530136]
  23. Bioinformatics. 2003 Aug 12;19(12):1572-4 [PMID: 12912839]
  24. J Mol Evol. 2001 Oct-Nov;53(4-5):477-84 [PMID: 11675608]
  25. Mol Biol Evol. 2005 Dec;22(12):2472-9 [PMID: 16107592]
  26. Bioinformatics. 2006 Nov 1;22(21):2688-90 [PMID: 16928733]
  27. Trends Ecol Evol. 1996 Sep;11(9):367-72 [PMID: 21237881]
  28. Bioinformatics. 2005 Feb 15;21(4):456-63 [PMID: 15608047]
  29. Bioinformatics. 2005 Jun;21 Suppl 1:i97-106 [PMID: 15961504]
  30. Syst Biol. 1997 Dec;46(4):590-621 [PMID: 11975335]
  31. Genome Res. 2004 Dec;14(12):2412-23 [PMID: 15574820]
  32. Syst Biol. 2001 Aug;50(4):525-39 [PMID: 12116651]
  33. PLoS Comput Biol. 2006 Jun 23;2(6):e69 [PMID: 16789817]
  34. Syst Biol. 2010 May;59(3):307-21 [PMID: 20525638]
  35. Genome Biol. 2008 Oct 30;9(10):235 [PMID: 18983710]

MeSH Term

Algorithms
Artificial Intelligence
Computational Biology
Internet
Likelihood Functions
Phylogeny
Software

Word Cloud

Created with Highcharts 10.0.0MetaPIGAv20stochasticheuristicslargephylogenyinferencealgorithmGeneticmetaGAsubstitutionmodelsdatatreesimplementedrobustsequencessoftwareparametersfunctionalitiesmaximumlikelihoodclassicalAlgorithmtogetheralsoInformationCriterionselectionbatchfilesextensiveinterfacehighwellusingBACKGROUND:developmentlastdecadeapplicationsoftwaresmadekeystepcomparativestudiesinvolvingmolecularStillchoiceoftendictatedcombinationrelatedrawperformancesratherpracticalissuesergonomicsand/oravailabilityspecificRESULTS:presentimplementationseveralincludingSimulatedAnnealingMetapopulationcomplexdiscreteGammarateheterogeneitypossibilitypartitionimplementsLikelihoodRatioTestAkaikeBayesianautomatedbestfitHeuristicshighlycustomizablemanualcommandlineprocessingHoweveroffersgraphicalusersettinggeneratingrunningfollowingrunprogressmanipulatingresultusesstandardformatssetsplatformindependentruns3264-bitssystemstakesadvantagemultiprocessormulticorecomputersCONCLUSIONS:resolvesmajorprobleminherentAlgorithmsmaintaininginter-populationvariationevenstrongintra-populationImplementationadditionalsinglewillallowrigorousoptimizationheuristicmeaningfulcomparisonperformancesamongalgorithmsgivesaccesscustomizationphylogeneticistergonomicassistingnon-specialistsoundphylogeneticnucleotideuser-manualfreelyavailableacademicshttp://wwwmetapigaorg0:estimationmetapopulationgenetic

Similar Articles

Cited By