Hasan H Otu1, Khalid Sayood. 1. Department of Electrical Engineering, University of Nebraska-Lincoln, 209N WSEC, Lincoln, NE 68503, USA. hotu@bidmc.harvard.edu
Abstract
MOTIVATION: Most existing approaches for phylogenetic inference use multiple alignment of sequences and assume some sort of an evolutionary model. The multiple alignment strategy does not work for all types of data, e.g. whole genome phylogeny, and the evolutionary models may not always be correct. We propose a new sequence distance measure based on the relative information between the sequences using Lempel-Ziv complexity. The distance matrix thus obtained can be used to construct phylogenetic trees. RESULTS: The proposed approach does not require sequence alignment and is totally automatic. The algorithm has successfully constructed consistent phylogenies for real and simulated data sets. AVAILABILITY: Available on request from the authors.
MOTIVATION: Most existing approaches for phylogenetic inference use multiple alignment of sequences and assume some sort of an evolutionary model. The multiple alignment strategy does not work for all types of data, e.g. whole genome phylogeny, and the evolutionary models may not always be correct. We propose a new sequence distance measure based on the relative information between the sequences using Lempel-Ziv complexity. The distance matrix thus obtained can be used to construct phylogenetic trees. RESULTS: The proposed approach does not require sequence alignment and is totally automatic. The algorithm has successfully constructed consistent phylogenies for real and simulated data sets. AVAILABILITY: Available on request from the authors.
Authors: Markus Göker; Guido W Grimm; Alexander F Auch; Ralf Aurahs; Michal Kučera Journal: Evol Bioinform Online Date: 2010-09-09 Impact factor: 1.625