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  Dashboard > Bioinformatics > ... > Bioinformatics Software > PHYLIP
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PHYLIP

PHYLIP (PHYLogeny Inference Package)

New version coming soon!

PHYLIP is a package of programs for inferring phylogenies (evolutionary trees). Methods that are available in the package include parsimony, distance matrix, and likelihood methods, including bootstrapping and consensus trees. Data type that can be handled include molecular sequences, gene frequencies, restriction sites, and distance matrices

  • Programs for Molecular Sequence Data:
    • Protpars - Protein parsimony
    • Dnacomp - Compatibility for DNA
    • Dnaml - Maximum likelihood method
    • Dnadist - Distances from sequences
    • Dnapars - Parsimony method for DNA
    • Dnapenny - Branch and bound for DNA
    • Dnainvar - Phylogenetic invariants
    • Dnamlk - DNA ML with molecular clock
    • Restml - ML for restriction sites
    • Protdist - Distances from proteins
    • Seqboot - Bootstraps sequence data sets
  • Programs for Distance Matrix Data:
    • Fitch - Fitch-Margoliash and least-squares methods
    • Kitsch - Fitch-Margoliash and least squares methods with evolutionary clock
    • Neighbor - Neighbor-joining and UPGMA methods
  • Programs for Gene Frequencies and Continuous Characters:
    • Contml - Maximum likelihood method
    • Gendist - Computes genetic distances
    • Factor - Recode multistate characters
  • Programs for 0-1 Discrete State Data:
    • Mix - Wagner, Camin-Sokal, and mixed parsimony criteria
    • Penny - Finds all most parsimonious trees by branch-and-bound
    • Dollop - Dollo and Polymorphism Parsimony Program
    • Dolpenny - Branch and bound to find all most parsimonious treesfor Dollo
    • Clique - Compatibility method
    • Factor - Recode multistate characters
  • Programs for plotting and consensus trees:
    • Consense - Majority-rule and strict consensus trees

Detail information on the PHYLIP project can be found at: PHYLIP

If you have any problems while using these tools, please email bioace-help at ccr.buffalo.edu

Center for Computational Research - University at Buffalo - State University of New York