PAUP* 4.0 : Phylogenetic Analysis Using Parsimony
- D. Swofford
- Computer Science
PAUP* 4.0 Beta is a major upgrade of the bestselling software for the inference of evolutionary trees, for use in Macintosh or Windows/DOS-based formats. This version is for use in Macintosh. Please…
AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics
A simple tool is presented that uses the output from MCMC simulations and visualizes a number of properties of primary interest in a Bayesian phylogenetic analysis, such as convergence rates of posterior split probabilities and branch lengths.
BIOSYS-1: a FORTRAN program for the comprehensive analysis of electrophoretic data in population genetics and systematics
Partitioning and combining data in phylogenetic analysis
BEAGLE: An Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics
BEAGLE, an application programming interface (API) and library for high-performance statistical phylogenetic inference, is presented, which provides a uniform interface for performing phylogenetic likelihood calculations on a variety of compute hardware platforms.
NEXUS: an extensible file format for systematic information.
The goals of the format are to allow future expansion, to include diverse kinds of information, to be independent of particular computer operating systems, and to be easily processed by a program.
Inferring Evolutionary Trees with PAUP*
- J. Wilgenbusch, D. Swofford
- Biology, Computer ScienceCurrent Protocols in Bioinformatics
- 1 January 2003
This unit provides a general description of reconstructing evolutionary trees using PAUP* 4.0 using an example analysis of mitochondrial DNA sequence data using the parsimony and the likelihood criteria to infer optimal trees.
Reconstructing ancestral character states under Wagner parsimony
A compound poisson process for relaxing the molecular clock.
This work introduces a parametric model that relaxes the molecular clock by allowing rates to vary across lineages according to a compound Poisson process and uses Markov chain Monte Carlo integration to evaluate the posterior probability distribution.
Inferring Evolutionary Trees from Gene Frequency Data Under the Principle of Maximum Parsimony
A new method for inferring evolutionary trees from gene frequency data is described that avoids limitations by enforcing biologically reasonable constraints without discarding the frequency information and appears to be free of logical difficulties affecting a variety of other parsimony methods.