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Finding all maximal perfect haplotype blocks in linear time
Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals’ haplotype data, however, require excessive computing times and...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7008532/ https://www.ncbi.nlm.nih.gov/pubmed/32055252 http://dx.doi.org/10.1186/s13015-020-0163-6 |
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author | Alanko, Jarno Bannai, Hideo Cazaux, Bastien Peterlongo, Pierre Stoye, Jens |
author_facet | Alanko, Jarno Bannai, Hideo Cazaux, Bastien Peterlongo, Pierre Stoye, Jens |
author_sort | Alanko, Jarno |
collection | PubMed |
description | Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals’ haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al. (Advances in bioinformatics and computational biology: 11th Brazilian symposium on bioinformatics, BSB 2018, Niterói, Brazil, October 30 - November 1, 2018, Proceedings, 2018. 10.1007/978-3-030-01722-4_3) suggested the maximal perfect haplotype block as a very simple combinatorial pattern, forming the basis of a new method to perform rapid genome-wide selection scans. The algorithm they presented for identifying these blocks, however, had a worst-case running time quadratic in the genome length. It was posed as an open problem whether an optimal, linear-time algorithm exists. In this paper we give two algorithms that achieve this time bound, one conceptually very simple one using suffix trees and a second one using the positional Burrows–Wheeler Transform, that is very efficient also in practice. |
format | Online Article Text |
id | pubmed-7008532 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70085322020-02-13 Finding all maximal perfect haplotype blocks in linear time Alanko, Jarno Bannai, Hideo Cazaux, Bastien Peterlongo, Pierre Stoye, Jens Algorithms Mol Biol Research Recent large-scale community sequencing efforts allow at an unprecedented level of detail the identification of genomic regions that show signatures of natural selection. Traditional methods for identifying such regions from individuals’ haplotype data, however, require excessive computing times and therefore are not applicable to current datasets. In 2019, Cunha et al. (Advances in bioinformatics and computational biology: 11th Brazilian symposium on bioinformatics, BSB 2018, Niterói, Brazil, October 30 - November 1, 2018, Proceedings, 2018. 10.1007/978-3-030-01722-4_3) suggested the maximal perfect haplotype block as a very simple combinatorial pattern, forming the basis of a new method to perform rapid genome-wide selection scans. The algorithm they presented for identifying these blocks, however, had a worst-case running time quadratic in the genome length. It was posed as an open problem whether an optimal, linear-time algorithm exists. In this paper we give two algorithms that achieve this time bound, one conceptually very simple one using suffix trees and a second one using the positional Burrows–Wheeler Transform, that is very efficient also in practice. BioMed Central 2020-02-10 /pmc/articles/PMC7008532/ /pubmed/32055252 http://dx.doi.org/10.1186/s13015-020-0163-6 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Alanko, Jarno Bannai, Hideo Cazaux, Bastien Peterlongo, Pierre Stoye, Jens Finding all maximal perfect haplotype blocks in linear time |
title | Finding all maximal perfect haplotype blocks in linear time |
title_full | Finding all maximal perfect haplotype blocks in linear time |
title_fullStr | Finding all maximal perfect haplotype blocks in linear time |
title_full_unstemmed | Finding all maximal perfect haplotype blocks in linear time |
title_short | Finding all maximal perfect haplotype blocks in linear time |
title_sort | finding all maximal perfect haplotype blocks in linear time |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7008532/ https://www.ncbi.nlm.nih.gov/pubmed/32055252 http://dx.doi.org/10.1186/s13015-020-0163-6 |
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