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MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues

BACKGROUND: Sequence alignment is one of the most important techniques to analyze biological systems. It is also true that the alignment is not complete and we have to develop it to look for more accurate method. In particular, an alignment for homologous sequences with low sequence similarity is no...

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Autores principales: Hara, Toshihide, Sato, Keiko, Ohya, Masanori
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875243/
https://www.ncbi.nlm.nih.gov/pubmed/20459682
http://dx.doi.org/10.1186/1471-2105-11-235
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author Hara, Toshihide
Sato, Keiko
Ohya, Masanori
author_facet Hara, Toshihide
Sato, Keiko
Ohya, Masanori
author_sort Hara, Toshihide
collection PubMed
description BACKGROUND: Sequence alignment is one of the most important techniques to analyze biological systems. It is also true that the alignment is not complete and we have to develop it to look for more accurate method. In particular, an alignment for homologous sequences with low sequence similarity is not in satisfactory level. Usual methods for aligning protein sequences in recent years use a measure empirically determined. As an example, a measure is usually defined by a combination of two quantities (1) and (2) below: (1) the sum of substitutions between two residue segments, (2) the sum of gap penalties in insertion/deletion region. Such a measure is determined on the assumption that there is no an intersite correlation on the sequences. In this paper, we improve the alignment by taking the correlation of consecutive residues. RESULTS: We introduced a new method of alignment, called MTRAP by introducing a metric defined on compound systems of two sequences. In the benchmark tests by PREFAB 4.0 and HOMSTRAD, our pairwise alignment method gives higher accuracy than other methods such as ClustalW2, TCoffee, MAFFT. Especially for the sequences with sequence identity less than 15%, our method improves the alignment accuracy significantly. Moreover, we also showed that our algorithm works well together with a consistency-based progressive multiple alignment by modifying the TCoffee to use our measure. CONCLUSIONS: We indicated that our method leads to a significant increase in alignment accuracy compared with other methods. Our improvement is especially clear in low identity range of sequences. The source code is available at our web page, whose address is found in the section "Availability and requirements".
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spelling pubmed-28752432010-05-25 MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues Hara, Toshihide Sato, Keiko Ohya, Masanori BMC Bioinformatics Software BACKGROUND: Sequence alignment is one of the most important techniques to analyze biological systems. It is also true that the alignment is not complete and we have to develop it to look for more accurate method. In particular, an alignment for homologous sequences with low sequence similarity is not in satisfactory level. Usual methods for aligning protein sequences in recent years use a measure empirically determined. As an example, a measure is usually defined by a combination of two quantities (1) and (2) below: (1) the sum of substitutions between two residue segments, (2) the sum of gap penalties in insertion/deletion region. Such a measure is determined on the assumption that there is no an intersite correlation on the sequences. In this paper, we improve the alignment by taking the correlation of consecutive residues. RESULTS: We introduced a new method of alignment, called MTRAP by introducing a metric defined on compound systems of two sequences. In the benchmark tests by PREFAB 4.0 and HOMSTRAD, our pairwise alignment method gives higher accuracy than other methods such as ClustalW2, TCoffee, MAFFT. Especially for the sequences with sequence identity less than 15%, our method improves the alignment accuracy significantly. Moreover, we also showed that our algorithm works well together with a consistency-based progressive multiple alignment by modifying the TCoffee to use our measure. CONCLUSIONS: We indicated that our method leads to a significant increase in alignment accuracy compared with other methods. Our improvement is especially clear in low identity range of sequences. The source code is available at our web page, whose address is found in the section "Availability and requirements". BioMed Central 2010-05-08 /pmc/articles/PMC2875243/ /pubmed/20459682 http://dx.doi.org/10.1186/1471-2105-11-235 Text en Copyright ©2010 Hara et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Hara, Toshihide
Sato, Keiko
Ohya, Masanori
MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
title MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
title_full MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
title_fullStr MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
title_full_unstemmed MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
title_short MTRAP: Pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
title_sort mtrap: pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875243/
https://www.ncbi.nlm.nih.gov/pubmed/20459682
http://dx.doi.org/10.1186/1471-2105-11-235
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