Maximum parsimony events detection is based on the Sankoff reconstruction method with adaptable cost matrix (Sankoff 1975).
The FPR used in the comparison is determined by the maximum parsimony method (i.e., the stochastic mapping detection cutoff is set to match the maximum parsimony's FPR).
Unweighted maximum parsimony analysis yielded five equally parsimonious trees.
A prevailing branch-site detection methodology is based on the maximum parsimony approach.
The maximum parsimony paradigm is a classical and prevalent approach for the detection of gene family gains and losses mapped on specific branches.
This suggests that birth and death models for gene family sizes should be integrated in co-evolutionary detection method, as was done within the maximum parsimony framework (Cordero et al., 2008).
Once aligned, maximum parsimony analysis can be performed.
Fig. 5 Maximum parsimony tree of arsB Permease sequences.
Primary sequences were analysed under neighbour-joining, maximum parsimony, maximum likelihood, and Bayesian approaches.
The alignment dataset was analyzed using maximum likelihood (ML), maximum parsimony (MP) and Bayesian methods.
