PHYLOGENETIC SUPERTREE CONSTRUCTION USING TRIPLETS

Abstract

Phylogenetics deals with evolutionary relatedness between various species. Origin of species can be established by studying this relationship. The central task in phylogenetics is to infer this relationship among a given set of species. These relationships are usually represented by a phylogenetic tree with the species of interest at the leaves and where the internal vertices of the tree represent ancestral species. The amount of available molecular data is increasing exponentially and, given the continual advances in sequencing techniques and throughput, this explosive growth will likely to continue Biologists assemble large multi-gene data set from available vast amount of data for use in phylogenetic analyses which imposes distinct computational challenges. As this biological data is vast it is infeasible to construct a large tree for analysis. As a result, supertree methods have been the focus of much research. Supertree methods comprise one approach to reconstructing large phylogenies, given estimated trees for overlapping subsets of the entire set of taxa, using various algorithmic techniques. Several supertree methods have previously been developed. In this report implementation of Triplet Inference and Local Inconsistency (TILI) and Triplet Supertree Heuristic algorithms has been done. Comparative study is carried out on the basis of execution time and Accuracy measurement. The obtained results infer that Triplet Supertree Heuristic algorithm is faster and accurate than the TILI.