Multidimensional scaling for phylogenetics

We study a novel approach to determine the phylogenetic tree based on multidimensional scaling and Euclidean Steiner minimum tree. Pairwise sequence alignment method is implemented to align the objects such as DNA sequences and then some evolutionary models are applied to get the estimated distance matrix. Given the distance matrix, multidimensional scaling is widely used to reconstruct the map which has coordinates of the data points in a lower-dimensional space while preserves the distance. We employ both Classical multidimensional scaling and Bayesian multidimensional scaling on the distance matrix to obtain the coordinates of the objects. Based on the coordinates, the Euclidean Steiner minimum tree could be constructed and served as a candidate for the phylogenetic tree. The result from the simulation study indicates that the use of the Euclidean Steiner minimum tree as a phylogenetic tree is feasible.