Title

A Greedy Alignment-Free Distance Estimator For Phylogenetic Inference

Keywords

Alignment-free methods; Phylogeny reconstruction; Sequence comparison

Abstract

Background: Alignment-free sequence comparison approaches have been garnering increasing interest in various data- and compute-intensive applications such as phylogenetic inference for large-scale sequences. While k-mer based methods are predominantly used in real applications, the average common substring (ACS) approach is emerging as one of the prominent alignment-free approaches. This ACS approach has been further generalized by some recent work, either greedily or exactly, by allowing a bounded number of mismatches in the common substrings. Results: We present ALFRED-G, a greedy alignment-free distance estimator for phylogenetic tree reconstruction based on the concept of the generalized ACS approach. In this algorithm, we have investigated a new heuristic to efficiently compute the lengths of common strings with mismatches allowed, and have further applied this heuristic to phylogeny reconstruction. Performance evaluation using real sequence datasets shows that our heuristic is able to reconstruct comparable, or even more accurate, phylogenetic tree topologies than the kmacs heuristic algorithm at highly competitive speed. Conclusions: ALFRED-G is an alignment-free heuristic for evolutionary distance estimation between two biological sequences. This algorithm is implemented in C++ and has been incorporated into our open-source ALFRED software package ( http://alurulab.cc.gatech.edu/phylo ).

Publication Date

6-7-2017

Publication Title

BMC Bioinformatics

Volume

18

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1186/s12859-017-1658-0

Socpus ID

85020218588 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85020218588

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