Detecting interspecific recombination with a pruned probabilistic divergence measure
Motivation: A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment in...
Gespeichert in:
| Veröffentlicht in: | Bioinformatics 2005-05, Vol.21 (9), p.1797-1806 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1806 |
|---|---|
| container_issue | 9 |
| container_start_page | 1797 |
| container_title | Bioinformatics |
| container_volume | 21 |
| creator | Husmeier, Dirk Wright, Frank Milne, Iain |
| description | Motivation: A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment increases or the sliding-window size decreases, the posterior distribution becomes increasingly diffuse. This diffusion blurs the probabilistic divergence signal and adversely affects the detection accuracy. The present study investigates how this shortcoming can be redeemed with a pruning method based on post-processing clustering, using the Robinson–Foulds distance as a metric in tree topology space. Results: An application of the proposed scheme to three synthetic and two real-world DNA sequence alignments illustrates the amount of improvement that can be obtained with the pruning method. The study also includes a comparison with two established recombination detection methods: Recpars and the DSS (difference of sum of squares) method. Availability: Software, data and further supplementary material are available at the following website: http://www.bioss.sari.ac.uk/~dirk/Supplements/ Contact: dirk@bioss.ac.uk |
| doi_str_mv | 10.1093/bioinformatics/bti151 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_67788187</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>67788187</sourcerecordid><originalsourceid>FETCH-LOGICAL-c480t-750b783d478a5e853f1f982a71c02c6e8f0d2db2b76e8858a08afe804b7bb2ff3</originalsourceid><addsrcrecordid>eNqFkV1LHDEUhkOpuFb9CS1Dob0bN5kkk8xlsa0riCIoiDchyZzYbGcyazLjx783sotLe-PVOXCe856PF6HPBB8R3NC58YMPboi9Hr1NczN6wskHtEdYjcsK8-ZjzmktSiYxnaFPKS0x5oQxtotmhHNRMUH30NVPGMGOPtwVPowQ0wqsd94WEezQGx-y_BCKRz_-KXSxilOANofBaOM7n_LsovUPEO8gWCh60GmKcIB2nO4SHG7iPrr-_evqeFGeXZycHv84K21eaiwFx0ZI2jIhNQfJqSOukZUWxOLK1iAdbqvWVEbkXHKpsdQOJGZGGFM5R_fR97VuXuh-gjSq3icLXacDDFNStRBSEineBYngjDAqM_j1P3A5TDHkIxRpZM0opk2G-BqycUgpglOr6HsdnxXB6tUc9a85am1O7vuyEZ9MD-22a-NGBr5tAJ2s7lzUwfq05WqRvyB45so1lw2Ap7e6jn_zyVRwtbi5VYvzE9oweqkW9AXhf613</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>198643039</pqid></control><display><type>article</type><title>Detecting interspecific recombination with a pruned probabilistic divergence measure</title><source>OUP_牛津大学出版社OA刊</source><source>MEDLINE</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Alma/SFX Local Collection</source><creator>Husmeier, Dirk ; Wright, Frank ; Milne, Iain</creator><creatorcontrib>Husmeier, Dirk ; Wright, Frank ; Milne, Iain</creatorcontrib><description>Motivation: A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment increases or the sliding-window size decreases, the posterior distribution becomes increasingly diffuse. This diffusion blurs the probabilistic divergence signal and adversely affects the detection accuracy. The present study investigates how this shortcoming can be redeemed with a pruning method based on post-processing clustering, using the Robinson–Foulds distance as a metric in tree topology space. Results: An application of the proposed scheme to three synthetic and two real-world DNA sequence alignments illustrates the amount of improvement that can be obtained with the pruning method. The study also includes a comparison with two established recombination detection methods: Recpars and the DSS (difference of sum of squares) method. Availability: Software, data and further supplementary material are available at the following website: http://www.bioss.sari.ac.uk/~dirk/Supplements/ Contact: dirk@bioss.ac.uk</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/bti151</identifier><identifier>PMID: 15572473</identifier><identifier>CODEN: BOINFP</identifier><language>eng</language><publisher>Oxford: Oxford University Press</publisher><subject>Algorithms ; Biological and medical sciences ; Cluster Analysis ; DNA Mutational Analysis - methods ; Evolution, Molecular ; Fundamental and applied biological sciences. Psychology ; General aspects ; Genetic Variation - genetics ; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) ; Models, Genetic ; Models, Statistical ; Pattern Recognition, Automated - methods ; Phylogeny ; Recombination, Genetic - genetics ; Sequence Alignment - methods ; Sequence Analysis, DNA - methods</subject><ispartof>Bioinformatics, 2005-05, Vol.21 (9), p.1797-1806</ispartof><rights>2005 INIST-CNRS</rights><rights>Copyright Oxford University Press(England) May 1, 2005</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c480t-750b783d478a5e853f1f982a71c02c6e8f0d2db2b76e8858a08afe804b7bb2ff3</citedby><cites>FETCH-LOGICAL-c480t-750b783d478a5e853f1f982a71c02c6e8f0d2db2b76e8858a08afe804b7bb2ff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16785875$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15572473$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Husmeier, Dirk</creatorcontrib><creatorcontrib>Wright, Frank</creatorcontrib><creatorcontrib>Milne, Iain</creatorcontrib><title>Detecting interspecific recombination with a pruned probabilistic divergence measure</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>Motivation: A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment increases or the sliding-window size decreases, the posterior distribution becomes increasingly diffuse. This diffusion blurs the probabilistic divergence signal and adversely affects the detection accuracy. The present study investigates how this shortcoming can be redeemed with a pruning method based on post-processing clustering, using the Robinson–Foulds distance as a metric in tree topology space. Results: An application of the proposed scheme to three synthetic and two real-world DNA sequence alignments illustrates the amount of improvement that can be obtained with the pruning method. The study also includes a comparison with two established recombination detection methods: Recpars and the DSS (difference of sum of squares) method. Availability: Software, data and further supplementary material are available at the following website: http://www.bioss.sari.ac.uk/~dirk/Supplements/ Contact: dirk@bioss.ac.uk</description><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Cluster Analysis</subject><subject>DNA Mutational Analysis - methods</subject><subject>Evolution, Molecular</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Genetic Variation - genetics</subject><subject>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</subject><subject>Models, Genetic</subject><subject>Models, Statistical</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Phylogeny</subject><subject>Recombination, Genetic - genetics</subject><subject>Sequence Alignment - methods</subject><subject>Sequence Analysis, DNA - methods</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkV1LHDEUhkOpuFb9CS1Dob0bN5kkk8xlsa0riCIoiDchyZzYbGcyazLjx783sotLe-PVOXCe856PF6HPBB8R3NC58YMPboi9Hr1NczN6wskHtEdYjcsK8-ZjzmktSiYxnaFPKS0x5oQxtotmhHNRMUH30NVPGMGOPtwVPowQ0wqsd94WEezQGx-y_BCKRz_-KXSxilOANofBaOM7n_LsovUPEO8gWCh60GmKcIB2nO4SHG7iPrr-_evqeFGeXZycHv84K21eaiwFx0ZI2jIhNQfJqSOukZUWxOLK1iAdbqvWVEbkXHKpsdQOJGZGGFM5R_fR97VuXuh-gjSq3icLXacDDFNStRBSEineBYngjDAqM_j1P3A5TDHkIxRpZM0opk2G-BqycUgpglOr6HsdnxXB6tUc9a85am1O7vuyEZ9MD-22a-NGBr5tAJ2s7lzUwfq05WqRvyB45so1lw2Ap7e6jn_zyVRwtbi5VYvzE9oweqkW9AXhf613</recordid><startdate>20050501</startdate><enddate>20050501</enddate><creator>Husmeier, Dirk</creator><creator>Wright, Frank</creator><creator>Milne, Iain</creator><general>Oxford University Press</general><general>Oxford Publishing Limited (England)</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7TM</scope><scope>7TO</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>H94</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>7X8</scope></search><sort><creationdate>20050501</creationdate><title>Detecting interspecific recombination with a pruned probabilistic divergence measure</title><author>Husmeier, Dirk ; Wright, Frank ; Milne, Iain</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c480t-750b783d478a5e853f1f982a71c02c6e8f0d2db2b76e8858a08afe804b7bb2ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Algorithms</topic><topic>Biological and medical sciences</topic><topic>Cluster Analysis</topic><topic>DNA Mutational Analysis - methods</topic><topic>Evolution, Molecular</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Genetic Variation - genetics</topic><topic>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</topic><topic>Models, Genetic</topic><topic>Models, Statistical</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Phylogeny</topic><topic>Recombination, Genetic - genetics</topic><topic>Sequence Alignment - methods</topic><topic>Sequence Analysis, DNA - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Husmeier, Dirk</creatorcontrib><creatorcontrib>Wright, Frank</creatorcontrib><creatorcontrib>Milne, Iain</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Husmeier, Dirk</au><au>Wright, Frank</au><au>Milne, Iain</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detecting interspecific recombination with a pruned probabilistic divergence measure</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2005-05-01</date><risdate>2005</risdate><volume>21</volume><issue>9</issue><spage>1797</spage><epage>1806</epage><pages>1797-1806</pages><issn>1367-4803</issn><eissn>1460-2059</eissn><eissn>1367-4811</eissn><coden>BOINFP</coden><abstract>Motivation: A promising sliding-window method for the detection of interspecific recombination in DNA sequence alignments is based on the monitoring of changes in the posterior distribution of tree topologies with a probabilistic divergence measure. However, as the number of taxa in the alignment increases or the sliding-window size decreases, the posterior distribution becomes increasingly diffuse. This diffusion blurs the probabilistic divergence signal and adversely affects the detection accuracy. The present study investigates how this shortcoming can be redeemed with a pruning method based on post-processing clustering, using the Robinson–Foulds distance as a metric in tree topology space. Results: An application of the proposed scheme to three synthetic and two real-world DNA sequence alignments illustrates the amount of improvement that can be obtained with the pruning method. The study also includes a comparison with two established recombination detection methods: Recpars and the DSS (difference of sum of squares) method. Availability: Software, data and further supplementary material are available at the following website: http://www.bioss.sari.ac.uk/~dirk/Supplements/ Contact: dirk@bioss.ac.uk</abstract><cop>Oxford</cop><pub>Oxford University Press</pub><pmid>15572473</pmid><doi>10.1093/bioinformatics/bti151</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1367-4803 |
| ispartof | Bioinformatics, 2005-05, Vol.21 (9), p.1797-1806 |
| issn | 1367-4803 1460-2059 1367-4811 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_67788187 |
| source | OUP_牛津大学出版社OA刊; MEDLINE; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Algorithms Biological and medical sciences Cluster Analysis DNA Mutational Analysis - methods Evolution, Molecular Fundamental and applied biological sciences. Psychology General aspects Genetic Variation - genetics Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Genetic Models, Statistical Pattern Recognition, Automated - methods Phylogeny Recombination, Genetic - genetics Sequence Alignment - methods Sequence Analysis, DNA - methods |
| title | Detecting interspecific recombination with a pruned probabilistic divergence measure |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T08%3A10%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Detecting%20interspecific%20recombination%20with%20a%20pruned%20probabilistic%20divergence%20measure&rft.jtitle=Bioinformatics&rft.au=Husmeier,%20Dirk&rft.date=2005-05-01&rft.volume=21&rft.issue=9&rft.spage=1797&rft.epage=1806&rft.pages=1797-1806&rft.issn=1367-4803&rft.eissn=1460-2059&rft.coden=BOINFP&rft_id=info:doi/10.1093/bioinformatics/bti151&rft_dat=%3Cproquest_cross%3E67788187%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=198643039&rft_id=info:pmid/15572473&rfr_iscdi=true |