These results show that the space of maximum parsimony solutions is complex and sensitive to the event costs, and thus, choosing ad hoc event costs may result in misrepresenting evolutionary histories.
In this paper, we propose a modified version of SHSD —XHSD—, that can efficiently find a solution for maximum parsimony xor-haplotyping problem and resolve the ambiguity with the help of a small number of regular genotypes.
From the maximum parsimony point of view, refining an xor-haplotyping solution via bit flipping method does not necessarily lead to global optimum unless the initial inference is a set-equivalent of the global optimal solution.
We used maximum parsimony (MP) to search for the most parsimonious trees, i.e., solutions that require the least amount of change.
Unweighted maximum parsimony analysis yielded five equally parsimonious trees.
For comparison, we then computed the maximum likelihood evolutionary histories (Definition 3.2) for several of the subgraphs induced by connected components of the parsimony solution.
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.
