Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic
HIV molecular epidemiology studies analyse viral pol gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the P...
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| Veröffentlicht in: | Scientific reports 2016-12, Vol.6 (1), p.39489-39489, Article 39489 |
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| creator | Yebra, Gonzalo Hodcroft, Emma B. Ragonnet-Cronin, Manon L. Pillay, Deenan Brown, Andrew J. Leigh Fraser, Christophe Kellam, Paul de Oliveira, Tulio Dennis, Ann Hoppe, Anne Kityo, Cissy Frampton, Dan Ssemwanga, Deogratius Tanser, Frank Keshani, Jagoda Lingappa, Jairam Herbeck, Joshua Wawer, Maria Essex, Max Cohen, Myron S. Paton, Nicholas Ratmann, Oliver Kaleebu, Pontiano Hayes, Richard Fidler, Sarah Quinn, Thomas Novitsky, Vladimir Haywards, Andrew Nastouli, Eleni Morris, Steven Clark, Duncan Kozlakidis, Zisis |
| description | HIV molecular epidemiology studies analyse viral
pol
gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (
gag
-
pol
-
env, gag
-
pol, gag, pol, env
and partial
pol
) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the
gag
-
pol
-
env
datasets showing the best performance and
gag
and partial
pol
sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences. |
| doi_str_mv | 10.1038/srep39489 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5180198</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1899447358</sourcerecordid><originalsourceid>FETCH-LOGICAL-c438t-1a0b168a71fa308a6d6d959a49c8137e6df3da2ef675f8b88ba60f787d622d263</originalsourceid><addsrcrecordid>eNplkV1LHTEQhkNRqlgv-gdKoDdW2DZfu5vcCCKtCoI3tbchJ5k9RrLJNtkVzr9v5NjDqc3NBObhmRlehD5S8pUSLr-VDBNXQqp36JgR0TaMM3aw9z9Cp6U8kfpapgRV79ERk4RIJdpj5B6Kj2scweSwwcMSQrOGmEbAN7e_cIHfC0QL2JnZYD9OOT1DwdPjJqSKbXAGm2KZ82JnnyL2ERtc_LgEM4PDMHkHo7cf0OFgQoHT13qCHn58_3l109zdX99eXd41VnA5N9SQFe2k6elgOJGmc51TrTJCWUl5D50buDMMhq5vB7mScmU6MvSydx1jjnX8BF1svdOyGsFZiHM2QU_ZjyZvdDJe_9uJ_lGv07NuqSRUySo4exXkVC8vsx59sRCCiZCWoqlsWS85EaSin9-gT2nJsZ5XKaWE6Hn7IvyypWxOpSY17JahRL_Ep3fxVfbT_vY78m9YFTjfAqW24hry3sj_bH8A4Iyl7w</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1899447358</pqid></control><display><type>article</type><title>Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic</title><source>Springer Open Access</source><source>MEDLINE</source><source>Nature Free</source><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><source>Free Full-Text Journals in Chemistry</source><source>EZB Electronic Journals Library</source><creator>Yebra, Gonzalo ; Hodcroft, Emma B. ; Ragonnet-Cronin, Manon L. ; Pillay, Deenan ; Brown, Andrew J. Leigh ; Fraser, Christophe ; Kellam, Paul ; de Oliveira, Tulio ; Dennis, Ann ; Hoppe, Anne ; Kityo, Cissy ; Frampton, Dan ; Ssemwanga, Deogratius ; Tanser, Frank ; Keshani, Jagoda ; Lingappa, Jairam ; Herbeck, Joshua ; Wawer, Maria ; Essex, Max ; Cohen, Myron S. ; Paton, Nicholas ; Ratmann, Oliver ; Kaleebu, Pontiano ; Hayes, Richard ; Fidler, Sarah ; Quinn, Thomas ; Novitsky, Vladimir ; Haywards, Andrew ; Nastouli, Eleni ; Morris, Steven ; Clark, Duncan ; Kozlakidis, Zisis</creator><creatorcontrib>Yebra, Gonzalo ; Hodcroft, Emma B. ; Ragonnet-Cronin, Manon L. ; Pillay, Deenan ; Brown, Andrew J. Leigh ; Fraser, Christophe ; Kellam, Paul ; de Oliveira, Tulio ; Dennis, Ann ; Hoppe, Anne ; Kityo, Cissy ; Frampton, Dan ; Ssemwanga, Deogratius ; Tanser, Frank ; Keshani, Jagoda ; Lingappa, Jairam ; Herbeck, Joshua ; Wawer, Maria ; Essex, Max ; Cohen, Myron S. ; Paton, Nicholas ; Ratmann, Oliver ; Kaleebu, Pontiano ; Hayes, Richard ; Fidler, Sarah ; Quinn, Thomas ; Novitsky, Vladimir ; Haywards, Andrew ; Nastouli, Eleni ; Morris, Steven ; Clark, Duncan ; Kozlakidis, Zisis ; PANGEA_HIV Consortium ; ICONIC Project</creatorcontrib><description>HIV molecular epidemiology studies analyse viral
pol
gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (
gag
-
pol
-
env, gag
-
pol, gag, pol, env
and partial
pol
) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the
gag
-
pol
-
env
datasets showing the best performance and
gag
and partial
pol
sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/srep39489</identifier><identifier>PMID: 28008945</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/114/739 ; 631/181/757 ; 692/699/255/1901 ; Cohort Studies ; Coverage ; Epidemics ; Epidemiology ; Genes ; Genes, env ; Genes, gag ; Genes, pol ; Genome, Viral ; Genomes ; HIV - genetics ; HIV Infections - epidemiology ; HIV Infections - virology ; Humanities and Social Sciences ; Humans ; Likelihood Functions ; Molecular Epidemiology ; multidisciplinary ; Nucleotide sequence ; Phylogeny ; Pol gene ; Regression Analysis ; Reproducibility of Results ; Sampling ; Science ; South Africa ; Trees ; United Kingdom</subject><ispartof>Scientific reports, 2016-12, Vol.6 (1), p.39489-39489, Article 39489</ispartof><rights>The Author(s) 2016</rights><rights>Copyright Nature Publishing Group Dec 2016</rights><rights>Copyright © 2016, The Author(s) 2016 The Author(s)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c438t-1a0b168a71fa308a6d6d959a49c8137e6df3da2ef675f8b88ba60f787d622d263</citedby><cites>FETCH-LOGICAL-c438t-1a0b168a71fa308a6d6d959a49c8137e6df3da2ef675f8b88ba60f787d622d263</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180198/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180198/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27903,27904,41099,42168,51554,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28008945$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yebra, Gonzalo</creatorcontrib><creatorcontrib>Hodcroft, Emma B.</creatorcontrib><creatorcontrib>Ragonnet-Cronin, Manon L.</creatorcontrib><creatorcontrib>Pillay, Deenan</creatorcontrib><creatorcontrib>Brown, Andrew J. Leigh</creatorcontrib><creatorcontrib>Fraser, Christophe</creatorcontrib><creatorcontrib>Kellam, Paul</creatorcontrib><creatorcontrib>de Oliveira, Tulio</creatorcontrib><creatorcontrib>Dennis, Ann</creatorcontrib><creatorcontrib>Hoppe, Anne</creatorcontrib><creatorcontrib>Kityo, Cissy</creatorcontrib><creatorcontrib>Frampton, Dan</creatorcontrib><creatorcontrib>Ssemwanga, Deogratius</creatorcontrib><creatorcontrib>Tanser, Frank</creatorcontrib><creatorcontrib>Keshani, Jagoda</creatorcontrib><creatorcontrib>Lingappa, Jairam</creatorcontrib><creatorcontrib>Herbeck, Joshua</creatorcontrib><creatorcontrib>Wawer, Maria</creatorcontrib><creatorcontrib>Essex, Max</creatorcontrib><creatorcontrib>Cohen, Myron S.</creatorcontrib><creatorcontrib>Paton, Nicholas</creatorcontrib><creatorcontrib>Ratmann, Oliver</creatorcontrib><creatorcontrib>Kaleebu, Pontiano</creatorcontrib><creatorcontrib>Hayes, Richard</creatorcontrib><creatorcontrib>Fidler, Sarah</creatorcontrib><creatorcontrib>Quinn, Thomas</creatorcontrib><creatorcontrib>Novitsky, Vladimir</creatorcontrib><creatorcontrib>Haywards, Andrew</creatorcontrib><creatorcontrib>Nastouli, Eleni</creatorcontrib><creatorcontrib>Morris, Steven</creatorcontrib><creatorcontrib>Clark, Duncan</creatorcontrib><creatorcontrib>Kozlakidis, Zisis</creatorcontrib><creatorcontrib>PANGEA_HIV Consortium</creatorcontrib><creatorcontrib>ICONIC Project</creatorcontrib><title>Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>HIV molecular epidemiology studies analyse viral
pol
gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (
gag
-
pol
-
env, gag
-
pol, gag, pol, env
and partial
pol
) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the
gag
-
pol
-
env
datasets showing the best performance and
gag
and partial
pol
sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.</description><subject>631/114/739</subject><subject>631/181/757</subject><subject>692/699/255/1901</subject><subject>Cohort Studies</subject><subject>Coverage</subject><subject>Epidemics</subject><subject>Epidemiology</subject><subject>Genes</subject><subject>Genes, env</subject><subject>Genes, gag</subject><subject>Genes, pol</subject><subject>Genome, Viral</subject><subject>Genomes</subject><subject>HIV - genetics</subject><subject>HIV Infections - epidemiology</subject><subject>HIV Infections - virology</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Likelihood Functions</subject><subject>Molecular Epidemiology</subject><subject>multidisciplinary</subject><subject>Nucleotide sequence</subject><subject>Phylogeny</subject><subject>Pol gene</subject><subject>Regression Analysis</subject><subject>Reproducibility of Results</subject><subject>Sampling</subject><subject>Science</subject><subject>South Africa</subject><subject>Trees</subject><subject>United Kingdom</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNplkV1LHTEQhkNRqlgv-gdKoDdW2DZfu5vcCCKtCoI3tbchJ5k9RrLJNtkVzr9v5NjDqc3NBObhmRlehD5S8pUSLr-VDBNXQqp36JgR0TaMM3aw9z9Cp6U8kfpapgRV79ERk4RIJdpj5B6Kj2scweSwwcMSQrOGmEbAN7e_cIHfC0QL2JnZYD9OOT1DwdPjJqSKbXAGm2KZ82JnnyL2ERtc_LgEM4PDMHkHo7cf0OFgQoHT13qCHn58_3l109zdX99eXd41VnA5N9SQFe2k6elgOJGmc51TrTJCWUl5D50buDMMhq5vB7mScmU6MvSydx1jjnX8BF1svdOyGsFZiHM2QU_ZjyZvdDJe_9uJ_lGv07NuqSRUySo4exXkVC8vsx59sRCCiZCWoqlsWS85EaSin9-gT2nJsZ5XKaWE6Hn7IvyypWxOpSY17JahRL_Ep3fxVfbT_vY78m9YFTjfAqW24hry3sj_bH8A4Iyl7w</recordid><startdate>20161223</startdate><enddate>20161223</enddate><creator>Yebra, Gonzalo</creator><creator>Hodcroft, Emma B.</creator><creator>Ragonnet-Cronin, Manon L.</creator><creator>Pillay, Deenan</creator><creator>Brown, Andrew J. Leigh</creator><creator>Fraser, Christophe</creator><creator>Kellam, Paul</creator><creator>de Oliveira, Tulio</creator><creator>Dennis, Ann</creator><creator>Hoppe, Anne</creator><creator>Kityo, Cissy</creator><creator>Frampton, Dan</creator><creator>Ssemwanga, Deogratius</creator><creator>Tanser, Frank</creator><creator>Keshani, Jagoda</creator><creator>Lingappa, Jairam</creator><creator>Herbeck, Joshua</creator><creator>Wawer, Maria</creator><creator>Essex, Max</creator><creator>Cohen, Myron S.</creator><creator>Paton, Nicholas</creator><creator>Ratmann, Oliver</creator><creator>Kaleebu, Pontiano</creator><creator>Hayes, Richard</creator><creator>Fidler, Sarah</creator><creator>Quinn, Thomas</creator><creator>Novitsky, Vladimir</creator><creator>Haywards, Andrew</creator><creator>Nastouli, Eleni</creator><creator>Morris, Steven</creator><creator>Clark, Duncan</creator><creator>Kozlakidis, Zisis</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</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>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20161223</creationdate><title>Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic</title><author>Yebra, Gonzalo ; Hodcroft, Emma B. ; Ragonnet-Cronin, Manon L. ; Pillay, Deenan ; Brown, Andrew J. Leigh ; Fraser, Christophe ; Kellam, Paul ; de Oliveira, Tulio ; Dennis, Ann ; Hoppe, Anne ; Kityo, Cissy ; Frampton, Dan ; Ssemwanga, Deogratius ; Tanser, Frank ; Keshani, Jagoda ; Lingappa, Jairam ; Herbeck, Joshua ; Wawer, Maria ; Essex, Max ; Cohen, Myron S. ; Paton, Nicholas ; Ratmann, Oliver ; Kaleebu, Pontiano ; Hayes, Richard ; Fidler, Sarah ; Quinn, Thomas ; Novitsky, Vladimir ; Haywards, Andrew ; Nastouli, Eleni ; Morris, Steven ; Clark, Duncan ; Kozlakidis, Zisis</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c438t-1a0b168a71fa308a6d6d959a49c8137e6df3da2ef675f8b88ba60f787d622d263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>631/114/739</topic><topic>631/181/757</topic><topic>692/699/255/1901</topic><topic>Cohort Studies</topic><topic>Coverage</topic><topic>Epidemics</topic><topic>Epidemiology</topic><topic>Genes</topic><topic>Genes, env</topic><topic>Genes, gag</topic><topic>Genes, pol</topic><topic>Genome, Viral</topic><topic>Genomes</topic><topic>HIV - genetics</topic><topic>HIV Infections - epidemiology</topic><topic>HIV Infections - virology</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Likelihood Functions</topic><topic>Molecular Epidemiology</topic><topic>multidisciplinary</topic><topic>Nucleotide sequence</topic><topic>Phylogeny</topic><topic>Pol gene</topic><topic>Regression Analysis</topic><topic>Reproducibility of Results</topic><topic>Sampling</topic><topic>Science</topic><topic>South Africa</topic><topic>Trees</topic><topic>United Kingdom</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yebra, Gonzalo</creatorcontrib><creatorcontrib>Hodcroft, Emma B.</creatorcontrib><creatorcontrib>Ragonnet-Cronin, Manon L.</creatorcontrib><creatorcontrib>Pillay, Deenan</creatorcontrib><creatorcontrib>Brown, Andrew J. 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Leigh</au><au>Fraser, Christophe</au><au>Kellam, Paul</au><au>de Oliveira, Tulio</au><au>Dennis, Ann</au><au>Hoppe, Anne</au><au>Kityo, Cissy</au><au>Frampton, Dan</au><au>Ssemwanga, Deogratius</au><au>Tanser, Frank</au><au>Keshani, Jagoda</au><au>Lingappa, Jairam</au><au>Herbeck, Joshua</au><au>Wawer, Maria</au><au>Essex, Max</au><au>Cohen, Myron S.</au><au>Paton, Nicholas</au><au>Ratmann, Oliver</au><au>Kaleebu, Pontiano</au><au>Hayes, Richard</au><au>Fidler, Sarah</au><au>Quinn, Thomas</au><au>Novitsky, Vladimir</au><au>Haywards, Andrew</au><au>Nastouli, Eleni</au><au>Morris, Steven</au><au>Clark, Duncan</au><au>Kozlakidis, Zisis</au><aucorp>PANGEA_HIV Consortium</aucorp><aucorp>ICONIC Project</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2016-12-23</date><risdate>2016</risdate><volume>6</volume><issue>1</issue><spage>39489</spage><epage>39489</epage><pages>39489-39489</pages><artnum>39489</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>HIV molecular epidemiology studies analyse viral
pol
gene sequences due to their availability, but whole genome sequencing allows to use other genes. We aimed to determine what gene(s) provide(s) the best approximation to the real phylogeny by analysing a simulated epidemic (created as part of the PANGEA_HIV project) with a known transmission tree. We sub-sampled a simulated dataset of 4662 sequences into different combinations of genes (
gag
-
pol
-
env, gag
-
pol, gag, pol, env
and partial
pol
) and sampling depths (100%, 60%, 20% and 5%), generating 100 replicates for each case. We built maximum-likelihood trees for each combination using RAxML (GTR + Γ), and compared their topologies to the corresponding true tree’s using CompareTree. The accuracy of the trees was significantly proportional to the length of the sequences used, with the
gag
-
pol
-
env
datasets showing the best performance and
gag
and partial
pol
sequences showing the worst. The lowest sampling depths (20% and 5%) greatly reduced the accuracy of tree reconstruction and showed high variability among replicates, especially when using the shortest gene datasets. In conclusion, using longer sequences derived from nearly whole genomes will improve the reliability of phylogenetic reconstruction. With low sample coverage, results can be highly variable, particularly when based on short sequences.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>28008945</pmid><doi>10.1038/srep39489</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2045-2322 |
| ispartof | Scientific reports, 2016-12, Vol.6 (1), p.39489-39489, Article 39489 |
| issn | 2045-2322 2045-2322 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5180198 |
| source | Springer Open Access; MEDLINE; Nature Free; DOAJ Directory of Open Access Journals; PubMed Central; Alma/SFX Local Collection; Free Full-Text Journals in Chemistry; EZB Electronic Journals Library |
| subjects | 631/114/739 631/181/757 692/699/255/1901 Cohort Studies Coverage Epidemics Epidemiology Genes Genes, env Genes, gag Genes, pol Genome, Viral Genomes HIV - genetics HIV Infections - epidemiology HIV Infections - virology Humanities and Social Sciences Humans Likelihood Functions Molecular Epidemiology multidisciplinary Nucleotide sequence Phylogeny Pol gene Regression Analysis Reproducibility of Results Sampling Science South Africa Trees United Kingdom |
| title | Using nearly full-genome HIV sequence data improves phylogeny reconstruction in a simulated epidemic |
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