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Automatic extraction of reliable regions from multiple sequence alignments

BACKGROUND: High quality multiple alignments are crucial in the transfer of annotation from one genome to another. Multiple alignment methods strive to achieve ever increasing levels of average accuracy on benchmark sets while the accuracy of individual alignments is often overlooked. RESULTS: We ha...

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Detalles Bibliográficos
Autores principales: Lassmann, Timo, Sonnhammer, Erik LL
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1892097/
https://www.ncbi.nlm.nih.gov/pubmed/17570868
http://dx.doi.org/10.1186/1471-2105-8-S5-S9
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author Lassmann, Timo
Sonnhammer, Erik LL
author_facet Lassmann, Timo
Sonnhammer, Erik LL
author_sort Lassmann, Timo
collection PubMed
description BACKGROUND: High quality multiple alignments are crucial in the transfer of annotation from one genome to another. Multiple alignment methods strive to achieve ever increasing levels of average accuracy on benchmark sets while the accuracy of individual alignments is often overlooked. RESULTS: We have previously developed a method to automatically assess the accuracy and overall difficulty of multiple alignments. This was achieved by a per-residue comparison between alternate alignments of the same sequences. Here we present a key extension to this method, an algorithm to extract similarly aligned regions from several alignments and merge them into a new consensus alignment. CONCLUSION: We demonstrate that the fraction of correctly aligned residues within the resulting alignments is increased by 25 – 100 percent compared to the original input alignments, as only the most reliably aligned parts are considered.
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spelling pubmed-18920972007-06-15 Automatic extraction of reliable regions from multiple sequence alignments Lassmann, Timo Sonnhammer, Erik LL BMC Bioinformatics Research BACKGROUND: High quality multiple alignments are crucial in the transfer of annotation from one genome to another. Multiple alignment methods strive to achieve ever increasing levels of average accuracy on benchmark sets while the accuracy of individual alignments is often overlooked. RESULTS: We have previously developed a method to automatically assess the accuracy and overall difficulty of multiple alignments. This was achieved by a per-residue comparison between alternate alignments of the same sequences. Here we present a key extension to this method, an algorithm to extract similarly aligned regions from several alignments and merge them into a new consensus alignment. CONCLUSION: We demonstrate that the fraction of correctly aligned residues within the resulting alignments is increased by 25 – 100 percent compared to the original input alignments, as only the most reliably aligned parts are considered. BioMed Central 2007-05-24 /pmc/articles/PMC1892097/ /pubmed/17570868 http://dx.doi.org/10.1186/1471-2105-8-S5-S9 Text en Copyright © 2007 Lassmann and Sonnhammer; 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 Research
Lassmann, Timo
Sonnhammer, Erik LL
Automatic extraction of reliable regions from multiple sequence alignments
title Automatic extraction of reliable regions from multiple sequence alignments
title_full Automatic extraction of reliable regions from multiple sequence alignments
title_fullStr Automatic extraction of reliable regions from multiple sequence alignments
title_full_unstemmed Automatic extraction of reliable regions from multiple sequence alignments
title_short Automatic extraction of reliable regions from multiple sequence alignments
title_sort automatic extraction of reliable regions from multiple sequence alignments
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1892097/
https://www.ncbi.nlm.nih.gov/pubmed/17570868
http://dx.doi.org/10.1186/1471-2105-8-S5-S9
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