A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison

Chun Li; Huan Liu; Junhong Liu; Yuping Qin; Zhifu Wang

doi:doi:10.11648/j.cbb.20140203.11

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A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison

Chun Li, Huan Liu, Junhong Liu, Yuping Qin, Zhifu Wang

Published in Computational Biology and Bioinformatics (Volume 2, Issue 3)

Received: 22 April 2014 Accepted: 15 May 2014 Published: 30 May 2014

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Abstract

Burrows-Wheeler Transform (BWT) is an extremely useful tool for textual lossless data compression. Recently, it has found many applications to bioinformatics. In this paper, BWT is introduced from the view of combinatorics, and then an equivalence relation on words is proposed which shows that the transformation captures some common features of equivalent words. Based on the rationale that to what extent two words differ can be evaluated by the factors excluding their common features, a matrix representation for a DNA sequence is defined by means of a “subtraction operation” between the original word and its BWT word, thus a DNA sequences is converted into a 24-D vector whose components are the spectral norms of such matrices. To illustrate the use of the quantitative characterization of DNA sequences, phylogenetic trees of the full β-globin genes of 15 species and the S segments of 13 hantaviruses are constructed. The resulting monophyletic clusters agree well with the established taxonomic groups.

Published in	Computational Biology and Bioinformatics (Volume 2, Issue 3)
DOI	10.11648/j.cbb.20140203.11
Page(s)	33-37
Creative Commons	This is an Open Access article, 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 or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

BWT, Elementary Row Operations, Equivalence, k-Word, Matrix Representation, Permutation, Phylogenetic Analysis

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APA Style

Chun Li, Huan Liu, Junhong Liu, Yuping Qin, Zhifu Wang. (2014). A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison. Computational Biology and Bioinformatics, 2(3), 33-37. https://doi.org/10.11648/j.cbb.20140203.11

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ACS Style

Chun Li; Huan Liu; Junhong Liu; Yuping Qin; Zhifu Wang. A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison. Comput. Biol. Bioinform. 2014, 2(3), 33-37. doi: 10.11648/j.cbb.20140203.11

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AMA Style

Chun Li, Huan Liu, Junhong Liu, Yuping Qin, Zhifu Wang. A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison. Comput Biol Bioinform. 2014;2(3):33-37. doi: 10.11648/j.cbb.20140203.11

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@article{10.11648/j.cbb.20140203.11,
  author = {Chun Li and Huan Liu and Junhong Liu and Yuping Qin and Zhifu Wang},
  title = {A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison},
  journal = {Computational Biology and Bioinformatics},
  volume = {2},
  number = {3},
  pages = {33-37},
  doi = {10.11648/j.cbb.20140203.11},
  url = {https://doi.org/10.11648/j.cbb.20140203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20140203.11},
  abstract = {Burrows-Wheeler Transform (BWT) is an extremely useful tool for textual lossless data compression. Recently, it has found many applications to bioinformatics. In this paper, BWT is introduced from the view of combinatorics, and then an equivalence relation on words is proposed which shows that the transformation captures some common features of equivalent words. Based on the rationale that to what extent two words differ can be evaluated by the factors excluding their common features, a matrix representation for a DNA sequence is defined by means of a “subtraction operation” between the original word and its BWT word, thus a DNA sequences is converted into a 24-D vector whose components are the spectral norms of such matrices. To illustrate the use of the quantitative characterization of DNA sequences, phylogenetic trees of the full β-globin genes of 15 species and the S segments of 13 hantaviruses are constructed. The resulting monophyletic clusters agree well with the established taxonomic groups.},
 year = {2014}
}

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TY  - JOUR
T1  - A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison
AU  - Chun Li
AU  - Huan Liu
AU  - Junhong Liu
AU  - Yuping Qin
AU  - Zhifu Wang
Y1  - 2014/05/30
PY  - 2014
N1  - https://doi.org/10.11648/j.cbb.20140203.11
DO  - 10.11648/j.cbb.20140203.11
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 33
EP  - 37
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20140203.11
AB  - Burrows-Wheeler Transform (BWT) is an extremely useful tool for textual lossless data compression. Recently, it has found many applications to bioinformatics. In this paper, BWT is introduced from the view of combinatorics, and then an equivalence relation on words is proposed which shows that the transformation captures some common features of equivalent words. Based on the rationale that to what extent two words differ can be evaluated by the factors excluding their common features, a matrix representation for a DNA sequence is defined by means of a “subtraction operation” between the original word and its BWT word, thus a DNA sequences is converted into a 24-D vector whose components are the spectral norms of such matrices. To illustrate the use of the quantitative characterization of DNA sequences, phylogenetic trees of the full β-globin genes of 15 species and the S segments of 13 hantaviruses are constructed. The resulting monophyletic clusters agree well with the established taxonomic groups.
VL  - 2
IS  - 3
ER  -

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Author Information

Chun Li

College of Mathematics and Physics, Bohai University, Jinzhou 121013 China; Food Safety Key Lab of Liaoning Province, Bohai University, Jinzhou 121013 China
Huan Liu

College of Mathematics and Physics, Bohai University, Jinzhou 121013 China
Junhong Liu

College of Mathematics and Physics, Bohai University, Jinzhou 121013 China
Yuping Qin

College of Engineering, Bohai University, Jinzhou 121013 China
Zhifu Wang

College of Mathematics and Physics, Bohai University, Jinzhou 121013 China

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Plain Text BibTeX RIS

APA Style

Chun Li, Huan Liu, Junhong Liu, Yuping Qin, Zhifu Wang. (2014). A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison. Computational Biology and Bioinformatics, 2(3), 33-37. https://doi.org/10.11648/j.cbb.20140203.11

Copy | Download

ACS Style

Chun Li; Huan Liu; Junhong Liu; Yuping Qin; Zhifu Wang. A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison. Comput. Biol. Bioinform. 2014, 2(3), 33-37. doi: 10.11648/j.cbb.20140203.11

Copy | Download

AMA Style

Chun Li, Huan Liu, Junhong Liu, Yuping Qin, Zhifu Wang. A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison. Comput Biol Bioinform. 2014;2(3):33-37. doi: 10.11648/j.cbb.20140203.11

Copy | Download

@article{10.11648/j.cbb.20140203.11,
  author = {Chun Li and Huan Liu and Junhong Liu and Yuping Qin and Zhifu Wang},
  title = {A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison},
  journal = {Computational Biology and Bioinformatics},
  volume = {2},
  number = {3},
  pages = {33-37},
  doi = {10.11648/j.cbb.20140203.11},
  url = {https://doi.org/10.11648/j.cbb.20140203.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cbb.20140203.11},
  abstract = {Burrows-Wheeler Transform (BWT) is an extremely useful tool for textual lossless data compression. Recently, it has found many applications to bioinformatics. In this paper, BWT is introduced from the view of combinatorics, and then an equivalence relation on words is proposed which shows that the transformation captures some common features of equivalent words. Based on the rationale that to what extent two words differ can be evaluated by the factors excluding their common features, a matrix representation for a DNA sequence is defined by means of a “subtraction operation” between the original word and its BWT word, thus a DNA sequences is converted into a 24-D vector whose components are the spectral norms of such matrices. To illustrate the use of the quantitative characterization of DNA sequences, phylogenetic trees of the full β-globin genes of 15 species and the S segments of 13 hantaviruses are constructed. The resulting monophyletic clusters agree well with the established taxonomic groups.},
 year = {2014}
}

Copy | Download

TY  - JOUR
T1  - A Burrows-Wheeler Transform Based Method for DNA Sequence Comparison
AU  - Chun Li
AU  - Huan Liu
AU  - Junhong Liu
AU  - Yuping Qin
AU  - Zhifu Wang
Y1  - 2014/05/30
PY  - 2014
N1  - https://doi.org/10.11648/j.cbb.20140203.11
DO  - 10.11648/j.cbb.20140203.11
T2  - Computational Biology and Bioinformatics
JF  - Computational Biology and Bioinformatics
JO  - Computational Biology and Bioinformatics
SP  - 33
EP  - 37
PB  - Science Publishing Group
SN  - 2330-8281
UR  - https://doi.org/10.11648/j.cbb.20140203.11
AB  - Burrows-Wheeler Transform (BWT) is an extremely useful tool for textual lossless data compression. Recently, it has found many applications to bioinformatics. In this paper, BWT is introduced from the view of combinatorics, and then an equivalence relation on words is proposed which shows that the transformation captures some common features of equivalent words. Based on the rationale that to what extent two words differ can be evaluated by the factors excluding their common features, a matrix representation for a DNA sequence is defined by means of a “subtraction operation” between the original word and its BWT word, thus a DNA sequences is converted into a 24-D vector whose components are the spectral norms of such matrices. To illustrate the use of the quantitative characterization of DNA sequences, phylogenetic trees of the full β-globin genes of 15 species and the S segments of 13 hantaviruses are constructed. The resulting monophyletic clusters agree well with the established taxonomic groups.
VL  - 2
IS  - 3
ER  -

Copy | Download