Alignment-free distance measure based on return time distribution for sequence analysis: applications to clustering, molecular phylogeny and subtyping.
Identifieur interne : 001D64 ( PubMed/Corpus ); précédent : 001D63; suivant : 001D65Alignment-free distance measure based on return time distribution for sequence analysis: applications to clustering, molecular phylogeny and subtyping.
Auteurs : Pandurang Kolekar ; Mohan Kale ; Urmila Kulkarni-KaleSource :
- Molecular phylogenetics and evolution [ 1095-9513 ] ; 2012.
English descriptors
- KwdEn :
- MESH :
- classification : Dengue Virus, Flaviviridae.
- methods : Sequence Analysis.
- Cluster Analysis, Computational Biology, Data Mining, Genome, Viral, Pattern Recognition, Automated, Phylogeny, Sequence Alignment.
Abstract
The data deluge in post-genomic era demands development of novel data mining tools. Existing molecular phylogeny analyses (MPAs) developed for individual gene/protein sequences are alignment-based. However, the size of genomic data and uncertainties associated with alignments, necessitate development of alignment-free methods for MPA. Derivation of distances between sequences is an important step in both, alignment-dependant and alignment-free methods. Various alignment-free distance measures based on oligo-nucleotide frequencies, information content, compression techniques, etc. have been proposed. However, these distance measures do not account for relative order of components viz. nucleotides or amino acids. A new distance measure, based on the concept of 'return time distribution' (RTD) of k-mers is proposed, which accounts for the sequence composition and their relative orders. Statistical parameters of RTDs are used to derive a distance function. The resultant distance matrix is used for clustering and phylogeny using Neighbor-joining. Its performance for MPA and subtyping was evaluated using simulated data generated by block-bootstrap, receiver operating characteristics and leave-one-out cross validation methods. The proposed method was successfully applied for MPA of family Flaviviridae and subtyping of Dengue viruses. It is observed that method retains resolution for classification and subtyping of viruses at varying levels of sequence similarity and taxonomic hierarchy.
DOI: 10.1016/j.ympev.2012.07.003
PubMed: 22820020
Links to Exploration step
pubmed:22820020Le document en format XML
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<author><name sortKey="Kolekar, Pandurang" sort="Kolekar, Pandurang" uniqKey="Kolekar P" first="Pandurang" last="Kolekar">Pandurang Kolekar</name>
<affiliation><nlm:affiliation>Bioinformatics Centre, University of Pune, Pune 411 007, India. pandurang@bioinfo.net.in</nlm:affiliation>
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<author><name sortKey="Kale, Mohan" sort="Kale, Mohan" uniqKey="Kale M" first="Mohan" last="Kale">Mohan Kale</name>
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<author><name sortKey="Kulkarni Kale, Urmila" sort="Kulkarni Kale, Urmila" uniqKey="Kulkarni Kale U" first="Urmila" last="Kulkarni-Kale">Urmila Kulkarni-Kale</name>
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<term>Dengue Virus (classification)</term>
<term>Flaviviridae (classification)</term>
<term>Genome, Viral</term>
<term>Pattern Recognition, Automated</term>
<term>Phylogeny</term>
<term>Sequence Alignment</term>
<term>Sequence Analysis (methods)</term>
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<front><div type="abstract" xml:lang="en">The data deluge in post-genomic era demands development of novel data mining tools. Existing molecular phylogeny analyses (MPAs) developed for individual gene/protein sequences are alignment-based. However, the size of genomic data and uncertainties associated with alignments, necessitate development of alignment-free methods for MPA. Derivation of distances between sequences is an important step in both, alignment-dependant and alignment-free methods. Various alignment-free distance measures based on oligo-nucleotide frequencies, information content, compression techniques, etc. have been proposed. However, these distance measures do not account for relative order of components viz. nucleotides or amino acids. A new distance measure, based on the concept of 'return time distribution' (RTD) of k-mers is proposed, which accounts for the sequence composition and their relative orders. Statistical parameters of RTDs are used to derive a distance function. The resultant distance matrix is used for clustering and phylogeny using Neighbor-joining. Its performance for MPA and subtyping was evaluated using simulated data generated by block-bootstrap, receiver operating characteristics and leave-one-out cross validation methods. The proposed method was successfully applied for MPA of family Flaviviridae and subtyping of Dengue viruses. It is observed that method retains resolution for classification and subtyping of viruses at varying levels of sequence similarity and taxonomic hierarchy.</div>
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<Abstract><AbstractText>The data deluge in post-genomic era demands development of novel data mining tools. Existing molecular phylogeny analyses (MPAs) developed for individual gene/protein sequences are alignment-based. However, the size of genomic data and uncertainties associated with alignments, necessitate development of alignment-free methods for MPA. Derivation of distances between sequences is an important step in both, alignment-dependant and alignment-free methods. Various alignment-free distance measures based on oligo-nucleotide frequencies, information content, compression techniques, etc. have been proposed. However, these distance measures do not account for relative order of components viz. nucleotides or amino acids. A new distance measure, based on the concept of 'return time distribution' (RTD) of k-mers is proposed, which accounts for the sequence composition and their relative orders. Statistical parameters of RTDs are used to derive a distance function. The resultant distance matrix is used for clustering and phylogeny using Neighbor-joining. Its performance for MPA and subtyping was evaluated using simulated data generated by block-bootstrap, receiver operating characteristics and leave-one-out cross validation methods. The proposed method was successfully applied for MPA of family Flaviviridae and subtyping of Dengue viruses. It is observed that method retains resolution for classification and subtyping of viruses at varying levels of sequence similarity and taxonomic hierarchy.</AbstractText>
<CopyrightInformation>Copyright © 2012 Elsevier Inc. All rights reserved.</CopyrightInformation>
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