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A greedy alignment-free distance estimator for phylogenetic inference
BACKGROUND: Alignment-free sequence comparison approaches have been garnering increasing interest in various data- and compute-intensive applications such as phylogenetic inference for large-scale sequences. While k-mer based methods are predominantly used in real applications, the average common su...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471951/ https://www.ncbi.nlm.nih.gov/pubmed/28617225 http://dx.doi.org/10.1186/s12859-017-1658-0 |
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author | Thankachan, Sharma V. Chockalingam, Sriram P. Liu, Yongchao Krishnan, Ambujam Aluru, Srinivas |
author_facet | Thankachan, Sharma V. Chockalingam, Sriram P. Liu, Yongchao Krishnan, Ambujam Aluru, Srinivas |
author_sort | Thankachan, Sharma V. |
collection | PubMed |
description | BACKGROUND: Alignment-free sequence comparison approaches have been garnering increasing interest in various data- and compute-intensive applications such as phylogenetic inference for large-scale sequences. While k-mer based methods are predominantly used in real applications, the average common substring (ACS) approach is emerging as one of the prominent alignment-free approaches. This ACS approach has been further generalized by some recent work, either greedily or exactly, by allowing a bounded number of mismatches in the common substrings. RESULTS: We present ALFRED-G, a greedy alignment-free distance estimator for phylogenetic tree reconstruction based on the concept of the generalized ACS approach. In this algorithm, we have investigated a new heuristic to efficiently compute the lengths of common strings with mismatches allowed, and have further applied this heuristic to phylogeny reconstruction. Performance evaluation using real sequence datasets shows that our heuristic is able to reconstruct comparable, or even more accurate, phylogenetic tree topologies than the kmacs heuristic algorithm at highly competitive speed. CONCLUSIONS: ALFRED-G is an alignment-free heuristic for evolutionary distance estimation between two biological sequences. This algorithm is implemented in C++ and has been incorporated into our open-source ALFRED software package (http://alurulab.cc.gatech.edu/phylo). |
format | Online Article Text |
id | pubmed-5471951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54719512017-06-19 A greedy alignment-free distance estimator for phylogenetic inference Thankachan, Sharma V. Chockalingam, Sriram P. Liu, Yongchao Krishnan, Ambujam Aluru, Srinivas BMC Bioinformatics Research BACKGROUND: Alignment-free sequence comparison approaches have been garnering increasing interest in various data- and compute-intensive applications such as phylogenetic inference for large-scale sequences. While k-mer based methods are predominantly used in real applications, the average common substring (ACS) approach is emerging as one of the prominent alignment-free approaches. This ACS approach has been further generalized by some recent work, either greedily or exactly, by allowing a bounded number of mismatches in the common substrings. RESULTS: We present ALFRED-G, a greedy alignment-free distance estimator for phylogenetic tree reconstruction based on the concept of the generalized ACS approach. In this algorithm, we have investigated a new heuristic to efficiently compute the lengths of common strings with mismatches allowed, and have further applied this heuristic to phylogeny reconstruction. Performance evaluation using real sequence datasets shows that our heuristic is able to reconstruct comparable, or even more accurate, phylogenetic tree topologies than the kmacs heuristic algorithm at highly competitive speed. CONCLUSIONS: ALFRED-G is an alignment-free heuristic for evolutionary distance estimation between two biological sequences. This algorithm is implemented in C++ and has been incorporated into our open-source ALFRED software package (http://alurulab.cc.gatech.edu/phylo). BioMed Central 2017-06-07 /pmc/articles/PMC5471951/ /pubmed/28617225 http://dx.doi.org/10.1186/s12859-017-1658-0 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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. |
spellingShingle | Research Thankachan, Sharma V. Chockalingam, Sriram P. Liu, Yongchao Krishnan, Ambujam Aluru, Srinivas A greedy alignment-free distance estimator for phylogenetic inference |
title | A greedy alignment-free distance estimator for phylogenetic inference |
title_full | A greedy alignment-free distance estimator for phylogenetic inference |
title_fullStr | A greedy alignment-free distance estimator for phylogenetic inference |
title_full_unstemmed | A greedy alignment-free distance estimator for phylogenetic inference |
title_short | A greedy alignment-free distance estimator for phylogenetic inference |
title_sort | greedy alignment-free distance estimator for phylogenetic inference |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471951/ https://www.ncbi.nlm.nih.gov/pubmed/28617225 http://dx.doi.org/10.1186/s12859-017-1658-0 |
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