Phylogenetics Software

PHYLIP and PAUP compete as the most widely used phylogenetic analysis software, although other newer applications such as PUZZLE are begiiming to compete. Here, PHYLIP and PAUP will be described in the most detail, with references made to other available packages that have useful features. However, the number of programs available is now so numerous, many each having their own useful features, that the 

According to the release notes accompanying PAUP test version 4, PAUP usually finds trees with likelihoods as high or higher [i.e., better] than PHYLIP (both because PAUP s tree rearrangements are more extensive and because its convergence criterion for branch-length iteration is stricter). 

PAUP performs the nonparametric bootstrap for distance, MP, and ML, using all options available for tree building with these methods. When a bootstrap or jackknife with MP is under way, MAXTREES should be set between 10 and no more than 

This is because poorly resolvable portions of an MP tree will usually be even less resolvable with resampled data hence, a replicate could find astronomical num- 

In addition, PAUP performs the Kishino-Hasegawa test to compare MP or ML trees, computes four types of consensus of multiple trees (usually used for multiple equal-length MP trees), computes stepwise differences between MP trees, and evaluates signal conflicts between specified partitions of sites (e.g., nuclear and organellar sequence data in a combined analysis). 

---

There are numerous computer software programs that permit one to investigate sequence ahgnment and phylogenetic relationships among (a) various proteins, domains, motifs, modules, etc., and (b) nucleic acid sequences in DNA and RNA. In addition to those presented below, various Internet-based algorithms afford rapid and convenient analysis of macromolecular sequences. 

Figure 1. Phylogenetic tree of P2A and 2 B subfamilies of Ca2+-transporting ATPases. Protein sequences of P-type ATPases of different species were aligned using ClustalW software and a phylogenetic tree was generated using TreeView. Three different branches representing die three main subtypes of Ca2+-ATPases are apparent SERCAs, PMCAs and SPCAs...

Phylogenetic analysis is the means of inferring or estimating evolutionary relationships. Nucleotide sequences of DNA or RNA and amino acid sequences of proteins are the most popular data used to construct phylogenetic trees. Methods of phylogenetic analysis using sequence data are introduced and performed with a software package, PHYLIP locally and online. 

The catalog of software programs for phylogenetic analyses is available at http //evolution.gentics.washington.edu/philip/software.html. 

Phylip (Phylogenetic Inference Package) is a software package comprising about 30 command-line programs that cover almost any aspect of phylogenetic analysis... 

Fig. 2.2 Phylogenetic relationship of type I PLAjS. The phylogenetic tree was generated from ClustalW alignment data using the GENETYX-MAC vlO.1.6 (Software Development Co., Ltd., Tokyo, Japan). 

Fig. 1. Phylogenetic trees for the groups of Alx, Prx, and Shox genes based on amino acid sequences of the homeodomains (top) and aristaless domains (below). DNAstar/Lasergene software was used to generate these trees, using Clustalv (PAM250). Shown as unbalanced branches, forcing branch distances to correspond to sequence divergence.

Tree-building methods implemented in available software are discussed in detail in the literature (Saitou, 1996 Swofford et al., 1996 Li, 1997) and described on the Internet. This section briefly describes some of the most popular methods. Treebuilding methods can be sorted into distance-based vs. character-based methods. Much of the discussion in molecular phylogenetics dwells on the utility of distance-and character-based methods (e.g., Saitou, 1996 Li, 1997). Distance methods compute pairwise distances according to some measure and then discard the actual data, using only the fixed distances to derive trees. Character-based methods derive trees that optimize the distribution of the actual data patterns for each character. Pairwise distances are, therefore, not flxed, as they are determined by the tree topology. The... 

The number of unique phylogenetic trees increases exponentially with the number of taxa, becoming astronomical even for, say, 50 sequences (Swofford et al., 1996 Li, 1997). In most cases, computational limitations permit exploration of only a small fraction of possible trees. The exact number will depend mainly on the nmnber of taxa, the optimality criterion (e.g., MP is much faster than ML), the parameters (e.g., unweighted MP is much faster than weighted ML with fewer preset parameters is much faster than with more and/or simultaneously optimized parameters), computer hardware, and computer software (some algorithms are faster than others some software allows multiprocessing some software limits the number and kind of trees that can be stored in memory). The search procediue is also affected by data structure poorly resolvable data produce more nearly optimal trees that must be evaluated to find the most optimal. 

---