Alignment-free Phylogenetic Tree Estimation

Autor: Nusrat Kabir Samia, Rifah Tamanna Usha, Anindita Kundu, Md. Mahbubur Rahman
Rok vydání: 2019
Předmět:
Zdroj: 2019 Innovations in Power and Advanced Computing Technologies (i-PACT).
Popis: Alignment free approaches for constructing phylogenetic tree have been developed and used widely in recent times. The construction of phylogenetic tree based on multiple sequence alignment or pairwise alignment is likely to consume more time and is less accurate than alignment-free methods. For this convenience, a large number of techniques have been implemented regarding alignment-free approaches. Accordingly, a clear concept of previous methods of alignment-free approach can pave the way for further development. In this paper, a detail analysis has been performed on three popular alignment-free methods based on the improvement of average common substring (ACS) which are kmacs, ALFRED-G, Spaced Seed. Evaluating the performances of these methods for various datasets, the pros and cons of each of these have been identified and a new method based on k-mer frequency has been proposed in this paper. Performance evaluation using real sequence datasets shows that in most of the cases our method is more accurate than Kmacs and Spaced Seed and in addition takes less time than all three algorithms- ALFRED-G, kmacs and Spaced Seed.
Databáze: OpenAIRE