Susana Vinga1, Jonas Almeida. 1. Department of Biometry & Epidemiology, Medical University of South Carolina, 135 Cannon Street, Suite 303, PO Box 250835, Charleston, SC 29425, USA.
Abstract
MOTIVATION: Genetic recombination and, in particular, genetic shuffling are at odds with sequence comparison by alignment, which assumes conservation of contiguity between homologous segments. A variety of theoretical foundations are being used to derive alignment-free methods that overcome this limitation. The formulation of alternative metrics for dissimilarity between sequences and their algorithmic implementations are reviewed. RESULTS: The overwhelming majority of work on alignment-free sequence has taken place in the past two decades, with most reports published in the past 5 years. Two main categories of methods have been proposed-methods based on word (oligomer) frequency, and methods that do not require resolving the sequence with fixed word length segments. The first category is based on the statistics of word frequency, on the distances defined in a Cartesian space defined by the frequency vectors, and on the information content of frequency distribution. The second category includes the use of Kolmogorov complexity and Chaos Theory. Despite their low visibility, alignment-free metrics are in fact already widely used as pre-selection filters for alignment-based querying of large applications. Recent work is furthering their usage as a scale-independent methodology that is capable of recognizing homology when loss of contiguity is beyond the possibility of alignment. AVAILABILITY: Most of the alignment-free algorithms reviewed were implemented in MATLAB code and are available at http://bioinformatics.musc.edu/resources.html
MOTIVATION: Genetic recombination and, in particular, genetic shuffling are at odds with sequence comparison by alignment, which assumes conservation of contiguity between homologous segments. A variety of theoretical foundations are being used to derive alignment-free methods that overcome this limitation. The formulation of alternative metrics for dissimilarity between sequences and their algorithmic implementations are reviewed. RESULTS: The overwhelming majority of work on alignment-free sequence has taken place in the past two decades, with most reports published in the past 5 years. Two main categories of methods have been proposed-methods based on word (oligomer) frequency, and methods that do not require resolving the sequence with fixed word length segments. The first category is based on the statistics of word frequency, on the distances defined in a Cartesian space defined by the frequency vectors, and on the information content of frequency distribution. The second category includes the use of Kolmogorov complexity and Chaos Theory. Despite their low visibility, alignment-free metrics are in fact already widely used as pre-selection filters for alignment-based querying of large applications. Recent work is furthering their usage as a scale-independent methodology that is capable of recognizing homology when loss of contiguity is beyond the possibility of alignment. AVAILABILITY: Most of the alignment-free algorithms reviewed were implemented in MATLAB code and are available at http://bioinformatics.musc.edu/resources.html
Authors: Denis A Malyshev; Kirandeep Dhami; Henry T Quach; Thomas Lavergne; Phillip Ordoukhanian; Ali Torkamani; Floyd E Romesberg Journal: Proc Natl Acad Sci U S A Date: 2012-07-06 Impact factor: 11.205