Estimating evolutionary distances between genomic sequences from spaced-word matches.
Identifieur interne : 001041 ( Ncbi/Merge ); précédent : 001040; suivant : 001042Estimating evolutionary distances between genomic sequences from spaced-word matches.
Auteurs : Burkhard Morgenstern [France] ; Bingyao Zhu [Allemagne] ; Sebastian Horwege [Allemagne] ; Chris André Leimeister [Allemagne]Source :
- Algorithms for molecular biology : AMB [ 1748-7188 ] ; 2015.
Abstract
Alignment-free methods are increasingly used to calculate evolutionary distances between DNA and protein sequences as a basis of phylogeny reconstruction. Most of these methods, however, use heuristic distance functions that are not based on any explicit model of molecular evolution. Herein, we propose a simple estimator d N of the evolutionary distance between two DNA sequences that is calculated from the number N of (spaced) word matches between them. We show that this distance function is more accurate than other distance measures that are used by alignment-free methods. In addition, we calculate the variance of the normalized number N of (spaced) word matches. We show that the variance of N is smaller for spaced words than for contiguous words, and that the variance is further reduced if our spaced-words approach is used with multiple patterns of 'match positions' and 'don't care positions'. Our software is available online and as downloadable source code at: http://spaced.gobics.de/.
DOI: 10.1186/s13015-015-0032-x
PubMed: 25685176
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Université d'Evry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA 23 Boulevard de France, Evry, 91037 France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen, 37073 Germany ; Université d'Evry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA 23 Boulevard de France, Evry</wicri:regionArea><placeName><region type="region">Île-de-France</region><region type="old region">Île-de-France</region><settlement type="city">Évry (Essonne)</settlement></placeName></affiliation></author><author><name sortKey="Zhu, Bingyao" sort="Zhu, Bingyao" uniqKey="Zhu B" first="Bingyao" last="Zhu">Bingyao Zhu</name><affiliation wicri:level="3"><nlm:affiliation>University of Göttingen, Department of General Microbiology, Grisebachstr. 8, Göttingen, 37073 Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>University of Göttingen, Department of General Microbiology, Grisebachstr. 8, Göttingen</wicri:regionArea><placeName><region type="land" nuts="2">Basse-Saxe</region><settlement type="city">Göttingen</settlement></placeName></affiliation></author><author><name sortKey="Horwege, Sebastian" sort="Horwege, Sebastian" uniqKey="Horwege S" first="Sebastian" last="Horwege">Sebastian Horwege</name><affiliation wicri:level="3"><nlm:affiliation>University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen, 37073 Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen</wicri:regionArea><placeName><region type="land" nuts="2">Basse-Saxe</region><settlement type="city">Göttingen</settlement></placeName></affiliation></author><author><name sortKey="Leimeister, Chris Andre" sort="Leimeister, Chris Andre" uniqKey="Leimeister C" first="Chris André" last="Leimeister">Chris André Leimeister</name><affiliation wicri:level="3"><nlm:affiliation>University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen, 37073 Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen</wicri:regionArea><placeName><region type="land" nuts="2">Basse-Saxe</region><settlement type="city">Göttingen</settlement></placeName></affiliation></author></analytic><series><title level="j">Algorithms for molecular biology : AMB</title><idno type="ISSN">1748-7188</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Alignment-free methods are increasingly used to calculate evolutionary distances between DNA and protein sequences as a basis of phylogeny reconstruction. Most of these methods, however, use heuristic distance functions that are not based on any explicit model of molecular evolution. Herein, we propose a simple estimator d N of the evolutionary distance between two DNA sequences that is calculated from the number N of (spaced) word matches between them. We show that this distance function is more accurate than other distance measures that are used by alignment-free methods. In addition, we calculate the variance of the normalized number N of (spaced) word matches. We show that the variance of N is smaller for spaced words than for contiguous words, and that the variance is further reduced if our spaced-words approach is used with multiple patterns of 'match positions' and 'don't care positions'. Our software is available online and as downloadable source code at: http://spaced.gobics.de/. </div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">25685176</PMID><DateCompleted><Year>2015</Year><Month>02</Month><Day>16</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1748-7188</ISSN><JournalIssue CitedMedium="Print"><Volume>10</Volume><PubDate><Year>2015</Year></PubDate></JournalIssue><Title>Algorithms for molecular biology : AMB</Title><ISOAbbreviation>Algorithms Mol Biol</ISOAbbreviation></Journal><ArticleTitle>Estimating evolutionary distances between genomic sequences from spaced-word matches.</ArticleTitle><Pagination><MedlinePgn>5</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s13015-015-0032-x</ELocationID><Abstract><AbstractText>Alignment-free methods are increasingly used to calculate evolutionary distances between DNA and protein sequences as a basis of phylogeny reconstruction. Most of these methods, however, use heuristic distance functions that are not based on any explicit model of molecular evolution. Herein, we propose a simple estimator d N of the evolutionary distance between two DNA sequences that is calculated from the number N of (spaced) word matches between them. We show that this distance function is more accurate than other distance measures that are used by alignment-free methods. In addition, we calculate the variance of the normalized number N of (spaced) word matches. We show that the variance of N is smaller for spaced words than for contiguous words, and that the variance is further reduced if our spaced-words approach is used with multiple patterns of 'match positions' and 'don't care positions'. 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Morgenstern</name></region></country><country name="Allemagne"><region name="Basse-Saxe"><name sortKey="Zhu, Bingyao" sort="Zhu, Bingyao" uniqKey="Zhu B" first="Bingyao" last="Zhu">Bingyao Zhu</name></region><name sortKey="Horwege, Sebastian" sort="Horwege, Sebastian" uniqKey="Horwege S" first="Sebastian" last="Horwege">Sebastian Horwege</name><name sortKey="Leimeister, Chris Andre" sort="Leimeister, Chris Andre" uniqKey="Leimeister C" first="Chris André" last="Leimeister">Chris André Leimeister</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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