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Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm
Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850291/ https://www.ncbi.nlm.nih.gov/pubmed/29029186 http://dx.doi.org/10.1093/molbev/msx263 |
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author | Lam, Ha Minh Ratmann, Oliver Boni, Maciej F |
author_facet | Lam, Ha Minh Ratmann, Oliver Boni, Maciej F |
author_sort | Lam, Ha Minh |
collection | PubMed |
description | Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was introduced for an exact nonparametric mosaicism statistic that gave high-precision P values for putative recombinants. This exact computation meant that multiple-comparisons corrected P values also had high precision, which is crucial when performing millions or billions of tests in large databases. Here, we introduce an improvement to the algorithmic complexity of this computation from O(mn(3)) to O(mn(2)), where m and n are the numbers of recombination-informative sites in the candidate recombinant. This new computation allows for recombination analysis to be performed in alignments with thousands of polymorphic sites. Benchmark runs are presented on viral genome sequence alignments, new features are introduced, and applications outside recombination analysis are discussed. |
format | Online Article Text |
id | pubmed-5850291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-58502912018-03-23 Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm Lam, Ha Minh Ratmann, Oliver Boni, Maciej F Mol Biol Evol Methods Identifying recombinant sequences in an era of large genomic databases is challenging as it requires an efficient algorithm to identify candidate recombinants and parents, as well as appropriate statistical methods to correct for the large number of comparisons performed. In 2007, a computation was introduced for an exact nonparametric mosaicism statistic that gave high-precision P values for putative recombinants. This exact computation meant that multiple-comparisons corrected P values also had high precision, which is crucial when performing millions or billions of tests in large databases. Here, we introduce an improvement to the algorithmic complexity of this computation from O(mn(3)) to O(mn(2)), where m and n are the numbers of recombination-informative sites in the candidate recombinant. This new computation allows for recombination analysis to be performed in alignments with thousands of polymorphic sites. Benchmark runs are presented on viral genome sequence alignments, new features are introduced, and applications outside recombination analysis are discussed. Oxford University Press 2018-01 2017-10-03 /pmc/articles/PMC5850291/ /pubmed/29029186 http://dx.doi.org/10.1093/molbev/msx263 Text en © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Lam, Ha Minh Ratmann, Oliver Boni, Maciej F Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm |
title | Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm |
title_full | Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm |
title_fullStr | Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm |
title_full_unstemmed | Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm |
title_short | Improved Algorithmic Complexity for the 3SEQ Recombination Detection Algorithm |
title_sort | improved algorithmic complexity for the 3seq recombination detection algorithm |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5850291/ https://www.ncbi.nlm.nih.gov/pubmed/29029186 http://dx.doi.org/10.1093/molbev/msx263 |
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