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An efficient numerical representation of genome sequence: natural vector with covariance component
BACKGROUND: The characterization and comparison of microbial sequences, including archaea, bacteria, viruses and fungi, are very important to understand their evolutionary origin and the population relationship. Most methods are limited by the sequence length and lack of generality. The purpose of t...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206847/ https://www.ncbi.nlm.nih.gov/pubmed/35729905 http://dx.doi.org/10.7717/peerj.13544 |
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author | Sun, Nan Zhao, Xin Yau, Stephen S.-T. |
author_facet | Sun, Nan Zhao, Xin Yau, Stephen S.-T. |
author_sort | Sun, Nan |
collection | PubMed |
description | BACKGROUND: The characterization and comparison of microbial sequences, including archaea, bacteria, viruses and fungi, are very important to understand their evolutionary origin and the population relationship. Most methods are limited by the sequence length and lack of generality. The purpose of this study is to propose a general characterization method, and to study the classification and phylogeny of the existing datasets. METHODS: We present a new alignment-free method to represent and compare biological sequences. By adding the covariance between each two nucleotides, the new 18-dimensional natural vector successfully describes 24,250 genomic sequences and 95,542 DNA barcode sequences. The new numerical representation is used to study the classification and phylogenetic relationship of microbial sequences. RESULTS: First, the classification results validate that the six-dimensional covariance vector is necessary to characterize sequences. Then, the 18-dimensional natural vector is further used to conduct the similarity relationship between giant virus and archaea, bacteria, other viruses. The nearest distance calculation results reflect that the giant viruses are closer to bacteria in distribution of four nucleotides. The phylogenetic relationships of the three representative families, Mimiviridae, Pandoraviridae and Marsellieviridae from giant viruses are analyzed. The trees show that ten sequences of Mimiviridae are clustered with Pandoraviridae, and Mimiviridae is closer to the root of the tree than Marsellieviridae. The new developed alignment-free method can be computed very fast, which provides an effective numerical representation for the sequence of microorganisms. |
format | Online Article Text |
id | pubmed-9206847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92068472022-06-20 An efficient numerical representation of genome sequence: natural vector with covariance component Sun, Nan Zhao, Xin Yau, Stephen S.-T. PeerJ Bioinformatics BACKGROUND: The characterization and comparison of microbial sequences, including archaea, bacteria, viruses and fungi, are very important to understand their evolutionary origin and the population relationship. Most methods are limited by the sequence length and lack of generality. The purpose of this study is to propose a general characterization method, and to study the classification and phylogeny of the existing datasets. METHODS: We present a new alignment-free method to represent and compare biological sequences. By adding the covariance between each two nucleotides, the new 18-dimensional natural vector successfully describes 24,250 genomic sequences and 95,542 DNA barcode sequences. The new numerical representation is used to study the classification and phylogenetic relationship of microbial sequences. RESULTS: First, the classification results validate that the six-dimensional covariance vector is necessary to characterize sequences. Then, the 18-dimensional natural vector is further used to conduct the similarity relationship between giant virus and archaea, bacteria, other viruses. The nearest distance calculation results reflect that the giant viruses are closer to bacteria in distribution of four nucleotides. The phylogenetic relationships of the three representative families, Mimiviridae, Pandoraviridae and Marsellieviridae from giant viruses are analyzed. The trees show that ten sequences of Mimiviridae are clustered with Pandoraviridae, and Mimiviridae is closer to the root of the tree than Marsellieviridae. The new developed alignment-free method can be computed very fast, which provides an effective numerical representation for the sequence of microorganisms. PeerJ Inc. 2022-06-16 /pmc/articles/PMC9206847/ /pubmed/35729905 http://dx.doi.org/10.7717/peerj.13544 Text en © 2022 Sun et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Sun, Nan Zhao, Xin Yau, Stephen S.-T. An efficient numerical representation of genome sequence: natural vector with covariance component |
title | An efficient numerical representation of genome sequence: natural vector with covariance component |
title_full | An efficient numerical representation of genome sequence: natural vector with covariance component |
title_fullStr | An efficient numerical representation of genome sequence: natural vector with covariance component |
title_full_unstemmed | An efficient numerical representation of genome sequence: natural vector with covariance component |
title_short | An efficient numerical representation of genome sequence: natural vector with covariance component |
title_sort | efficient numerical representation of genome sequence: natural vector with covariance component |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206847/ https://www.ncbi.nlm.nih.gov/pubmed/35729905 http://dx.doi.org/10.7717/peerj.13544 |
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