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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Use of a novel non-parametric version of DEPTH to identify genomic regions associated with prostate cancer risk</title><author><name sortKey="Macinnis, Robert J" sort="Macinnis, Robert J" uniqKey="Macinnis R" first="Robert J." last="Macinnis">Robert J. Macinnis</name><affiliation><nlm:aff id="A1">Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Schmidt, Daniel F" sort="Schmidt, Daniel F" uniqKey="Schmidt D" first="Daniel F." last="Schmidt">Daniel F. Schmidt</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Makalic, Enes" sort="Makalic, Enes" uniqKey="Makalic E" first="Enes" last="Makalic">Enes Makalic</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Severi, Gianluca" sort="Severi, Gianluca" uniqKey="Severi G" first="Gianluca" last="Severi">Gianluca Severi</name><affiliation><nlm:aff id="A3">Human Genetics Foundation, Torino, Italy; Université Paris-Saclay, Univ. Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France; Gustave Roussy, F-94805, Villejuif, France</nlm:aff></affiliation></author><author><name sortKey="Fitzgerald, Liesel M" sort="Fitzgerald, Liesel M" uniqKey="Fitzgerald L" first="Liesel M." last="Fitzgerald">Liesel M. Fitzgerald</name><affiliation><nlm:aff id="A4">Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania</nlm:aff></affiliation></author><author><name sortKey="Reumann, Matthias" sort="Reumann, Matthias" uniqKey="Reumann M" first="Matthias" last="Reumann">Matthias Reumann</name><affiliation><nlm:aff id="A5">IBM Research - Zurich, Switzerland</nlm:aff></affiliation><affiliation><nlm:aff id="A6">UNU-MERIT (United Nations University – Maastricht Economic and Social Research Institute on Innovation and Technology) Maastricht University, Maastricht, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Kapuscinski, Miroslaw K" sort="Kapuscinski, Miroslaw K" uniqKey="Kapuscinski M" first="Miroslaw K." last="Kapuscinski">Miroslaw K. Kapuscinski</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Kowalczyk, Adam" sort="Kowalczyk, Adam" uniqKey="Kowalczyk A" first="Adam" last="Kowalczyk">Adam Kowalczyk</name><affiliation><nlm:aff id="A7">Warsaw University of Technology, Warsaw, Poland</nlm:aff></affiliation><affiliation><nlm:aff id="A8">School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia</nlm:aff></affiliation></author><author><name sortKey="Zhou, Zeyu" sort="Zhou, Zeyu" uniqKey="Zhou Z" first="Zeyu" last="Zhou">Zeyu Zhou</name><affiliation><nlm:aff id="A9">IBM Research – Australia, Carlton, Australia</nlm:aff></affiliation></author><author><name sortKey="Goudey, Benjamin W" sort="Goudey, Benjamin W" uniqKey="Goudey B" first="Benjamin W." last="Goudey">Benjamin W. Goudey</name><affiliation><nlm:aff id="A9">IBM Research – Australia, Carlton, Australia</nlm:aff></affiliation></author><author><name sortKey="Qian, Guoqi" sort="Qian, Guoqi" uniqKey="Qian G" first="Guoqi" last="Qian">Guoqi Qian</name><affiliation><nlm:aff id="A8">School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia</nlm:aff></affiliation></author><author><name sortKey="Bui, Quang M" sort="Bui, Quang M" uniqKey="Bui Q" first="Quang M." last="Bui">Quang M. Bui</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Park, Daniel J" sort="Park, Daniel J" uniqKey="Park D" first="Daniel J." last="Park">Daniel J. Park</name><affiliation><nlm:aff id="A10">Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, VIC, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A11">Melbourne Bioinformatics Platform, Victorian Life Sciences Computation Initiative, University of Melbourne, VIC, Australia</nlm:aff></affiliation></author><author><name sortKey="Freeman, Adam" sort="Freeman, Adam" uniqKey="Freeman A" first="Adam" last="Freeman">Adam Freeman</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Southey, Melissa C" sort="Southey, Melissa C" uniqKey="Southey M" first="Melissa C." last="Southey">Melissa C. Southey</name><affiliation><nlm:aff id="A10">Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, VIC, Australia</nlm:aff></affiliation></author><author><name sortKey="Al Olama, Ali Amin" sort="Al Olama, Ali Amin" uniqKey="Al Olama A" first="Ali Amin" last="Al Olama">Ali Amin Al Olama</name><affiliation><nlm:aff id="A12">Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Kote Jarai, Zsofia" sort="Kote Jarai, Zsofia" uniqKey="Kote Jarai Z" first="Zsofia" last="Kote-Jarai">Zsofia Kote-Jarai</name><affiliation><nlm:aff id="A13">The Institute of Cancer Research, London, UK</nlm:aff></affiliation></author><author><name sortKey="Eeles, Rosalind A" sort="Eeles, Rosalind A" uniqKey="Eeles R" first="Rosalind A" last="Eeles">Rosalind A. Eeles</name><affiliation><nlm:aff id="A13">The Institute of Cancer Research, London, UK</nlm:aff></affiliation><affiliation><nlm:aff id="A14">The Royal Marsden NHS Foundation Trust, Surrey, UK</nlm:aff></affiliation></author><author><name sortKey="Hopper, John L" sort="Hopper, John L" uniqKey="Hopper J" first="John L." last="Hopper">John L. Hopper</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A15">Department of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea</nlm:aff></affiliation></author><author><name sortKey="Giles, Graham G" sort="Giles, Graham G" uniqKey="Giles G" first="Graham G." last="Giles">Graham G. Giles</name><affiliation><nlm:aff id="A1">Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">27539266</idno><idno type="pmc">5232414</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5232414</idno><idno type="RBID">PMC:5232414</idno><idno type="doi">10.1158/1055-9965.EPI-16-0301</idno><date when="2016">2016</date><idno type="wicri:Area/Pmc/Corpus">002099</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">002099</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Use of a novel non-parametric version of DEPTH to identify genomic regions associated with prostate cancer risk</title><author><name sortKey="Macinnis, Robert J" sort="Macinnis, Robert J" uniqKey="Macinnis R" first="Robert J." last="Macinnis">Robert J. Macinnis</name><affiliation><nlm:aff id="A1">Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Schmidt, Daniel F" sort="Schmidt, Daniel F" uniqKey="Schmidt D" first="Daniel F." last="Schmidt">Daniel F. Schmidt</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Makalic, Enes" sort="Makalic, Enes" uniqKey="Makalic E" first="Enes" last="Makalic">Enes Makalic</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Severi, Gianluca" sort="Severi, Gianluca" uniqKey="Severi G" first="Gianluca" last="Severi">Gianluca Severi</name><affiliation><nlm:aff id="A3">Human Genetics Foundation, Torino, Italy; Université Paris-Saclay, Univ. Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France; Gustave Roussy, F-94805, Villejuif, France</nlm:aff></affiliation></author><author><name sortKey="Fitzgerald, Liesel M" sort="Fitzgerald, Liesel M" uniqKey="Fitzgerald L" first="Liesel M." last="Fitzgerald">Liesel M. Fitzgerald</name><affiliation><nlm:aff id="A4">Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania</nlm:aff></affiliation></author><author><name sortKey="Reumann, Matthias" sort="Reumann, Matthias" uniqKey="Reumann M" first="Matthias" last="Reumann">Matthias Reumann</name><affiliation><nlm:aff id="A5">IBM Research - Zurich, Switzerland</nlm:aff></affiliation><affiliation><nlm:aff id="A6">UNU-MERIT (United Nations University – Maastricht Economic and Social Research Institute on Innovation and Technology) Maastricht University, Maastricht, The Netherlands</nlm:aff></affiliation></author><author><name sortKey="Kapuscinski, Miroslaw K" sort="Kapuscinski, Miroslaw K" uniqKey="Kapuscinski M" first="Miroslaw K." last="Kapuscinski">Miroslaw K. Kapuscinski</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Kowalczyk, Adam" sort="Kowalczyk, Adam" uniqKey="Kowalczyk A" first="Adam" last="Kowalczyk">Adam Kowalczyk</name><affiliation><nlm:aff id="A7">Warsaw University of Technology, Warsaw, Poland</nlm:aff></affiliation><affiliation><nlm:aff id="A8">School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia</nlm:aff></affiliation></author><author><name sortKey="Zhou, Zeyu" sort="Zhou, Zeyu" uniqKey="Zhou Z" first="Zeyu" last="Zhou">Zeyu Zhou</name><affiliation><nlm:aff id="A9">IBM Research – Australia, Carlton, Australia</nlm:aff></affiliation></author><author><name sortKey="Goudey, Benjamin W" sort="Goudey, Benjamin W" uniqKey="Goudey B" first="Benjamin W." last="Goudey">Benjamin W. Goudey</name><affiliation><nlm:aff id="A9">IBM Research – Australia, Carlton, Australia</nlm:aff></affiliation></author><author><name sortKey="Qian, Guoqi" sort="Qian, Guoqi" uniqKey="Qian G" first="Guoqi" last="Qian">Guoqi Qian</name><affiliation><nlm:aff id="A8">School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia</nlm:aff></affiliation></author><author><name sortKey="Bui, Quang M" sort="Bui, Quang M" uniqKey="Bui Q" first="Quang M." last="Bui">Quang M. Bui</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Park, Daniel J" sort="Park, Daniel J" uniqKey="Park D" first="Daniel J." last="Park">Daniel J. Park</name><affiliation><nlm:aff id="A10">Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, VIC, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A11">Melbourne Bioinformatics Platform, Victorian Life Sciences Computation Initiative, University of Melbourne, VIC, Australia</nlm:aff></affiliation></author><author><name sortKey="Freeman, Adam" sort="Freeman, Adam" uniqKey="Freeman A" first="Adam" last="Freeman">Adam Freeman</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author><author><name sortKey="Southey, Melissa C" sort="Southey, Melissa C" uniqKey="Southey M" first="Melissa C." last="Southey">Melissa C. Southey</name><affiliation><nlm:aff id="A10">Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, VIC, Australia</nlm:aff></affiliation></author><author><name sortKey="Al Olama, Ali Amin" sort="Al Olama, Ali Amin" uniqKey="Al Olama A" first="Ali Amin" last="Al Olama">Ali Amin Al Olama</name><affiliation><nlm:aff id="A12">Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Kote Jarai, Zsofia" sort="Kote Jarai, Zsofia" uniqKey="Kote Jarai Z" first="Zsofia" last="Kote-Jarai">Zsofia Kote-Jarai</name><affiliation><nlm:aff id="A13">The Institute of Cancer Research, London, UK</nlm:aff></affiliation></author><author><name sortKey="Eeles, Rosalind A" sort="Eeles, Rosalind A" uniqKey="Eeles R" first="Rosalind A" last="Eeles">Rosalind A. Eeles</name><affiliation><nlm:aff id="A13">The Institute of Cancer Research, London, UK</nlm:aff></affiliation><affiliation><nlm:aff id="A14">The Royal Marsden NHS Foundation Trust, Surrey, UK</nlm:aff></affiliation></author><author><name sortKey="Hopper, John L" sort="Hopper, John L" uniqKey="Hopper J" first="John L." last="Hopper">John L. Hopper</name><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A15">Department of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea</nlm:aff></affiliation></author><author><name sortKey="Giles, Graham G" sort="Giles, Graham G" uniqKey="Giles G" first="Graham G." last="Giles">Graham G. Giles</name><affiliation><nlm:aff id="A1">Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia</nlm:aff></affiliation><affiliation><nlm:aff id="A2">Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</nlm:aff></affiliation></author></analytic><series><title level="j">Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology</title><idno type="ISSN">1055-9965</idno><idno type="eISSN">1538-7755</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec id="S1"><title>Background</title><p id="P1">We have developed a GWAS analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of contiguous markers (e.g. single nucleotide polymorphisms, SNPs) across the genome. DEPTH is a machine learning algorithm for feature ranking of ultra-high dimensional datasets, built from well-established statistical tools such as bootstrapping, penalised regression and decision trees. Unlike marginal regression, which considers each SNP individually, the key idea behind DEPTH is to rank groups of SNPs in terms of their joint strength of association with the outcome. Our aim was to compare the performance of DEPTH with that of standard logistic regression analysis.</p></sec><sec id="S2"><title>Methods</title><p id="P2">We selected 1,854 prostate cancer cases and 1,894 controls from the UK for whom 541,129 SNPs were measured using the Illumina Infinium HumanHap550 array. Confirmation was sought using 4,152 cases and 2,874 controls, ascertained from the UK and Australia, for whom 211,155 SNPs were measured using the iCOGS Illumina Infinium array.</p></sec><sec id="S3"><title>Results</title><p id="P3">From the DEPTH analysis we identified 14 regions associated with prostate cancer risk that had been reported previously; five of which would not have been identified by conventional logistic regression. We also identified 112 novel putative susceptibility regions.</p></sec><sec id="S4"><title>Conclusions</title><p id="P4">DEPTH can reveal new risk-associated regions that would not have been identified using a conventional logistic regression analysis of individual SNPs.</p></sec><sec id="S5"><title>Impact</title><p id="P5">This study demonstrates that the DEPTH algorithm could identify additional genetic susceptibility regions that merit further investigation.</p></sec></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">9200608</journal-id><journal-id journal-id-type="pubmed-jr-id">2299</journal-id><journal-id journal-id-type="nlm-ta">Cancer Epidemiol Biomarkers Prev</journal-id><journal-id journal-id-type="iso-abbrev">Cancer Epidemiol. Biomarkers Prev.</journal-id><journal-title-group><journal-title>Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology</journal-title></journal-title-group><issn pub-type="ppub">1055-9965</issn><issn pub-type="epub">1538-7755</issn></journal-meta><article-meta><article-id pub-id-type="pmid">27539266</article-id><article-id pub-id-type="pmc">5232414</article-id><article-id pub-id-type="doi">10.1158/1055-9965.EPI-16-0301</article-id><article-id pub-id-type="manuscript">NIHMS816648</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Use of a novel non-parametric version of DEPTH to identify genomic regions associated with prostate cancer risk</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>MacInnis</surname><given-names>Robert J.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Schmidt</surname><given-names>Daniel F.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Makalic</surname><given-names>Enes</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Severi</surname><given-names>Gianluca</given-names></name><xref ref-type="aff" rid="A3">3</xref></contrib><contrib contrib-type="author"><name><surname>FitzGerald</surname><given-names>Liesel M.</given-names></name><xref ref-type="aff" rid="A4">4</xref></contrib><contrib contrib-type="author"><name><surname>Reumann</surname><given-names>Matthias</given-names></name><xref ref-type="aff" rid="A5">5</xref><xref ref-type="aff" rid="A6">6</xref></contrib><contrib contrib-type="author"><name><surname>Kapuscinski</surname><given-names>Miroslaw K.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Kowalczyk</surname><given-names>Adam</given-names></name><xref ref-type="aff" rid="A7">7</xref><xref ref-type="aff" rid="A8">8</xref></contrib><contrib contrib-type="author"><name><surname>Zhou</surname><given-names>Zeyu</given-names></name><xref ref-type="aff" rid="A9">9</xref></contrib><contrib contrib-type="author"><name><surname>Goudey</surname><given-names>Benjamin W.</given-names></name><xref ref-type="aff" rid="A9">9</xref></contrib><contrib contrib-type="author"><name><surname>Qian</surname><given-names>Guoqi</given-names></name><xref ref-type="aff" rid="A8">8</xref></contrib><contrib contrib-type="author"><name><surname>Bui</surname><given-names>Quang M.</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Park</surname><given-names>Daniel J.</given-names></name><xref ref-type="aff" rid="A10">10</xref><xref ref-type="aff" rid="A11">11</xref></contrib><contrib contrib-type="author"><name><surname>Freeman</surname><given-names>Adam</given-names></name><xref ref-type="aff" rid="A2">2</xref></contrib><contrib contrib-type="author"><name><surname>Southey</surname><given-names>Melissa C.</given-names></name><xref ref-type="aff" rid="A10">10</xref></contrib><contrib contrib-type="author"><name><surname>Al Olama</surname><given-names>Ali Amin</given-names></name><xref ref-type="aff" rid="A12">12</xref></contrib><contrib contrib-type="author"><name><surname>Kote-Jarai</surname><given-names>Zsofia</given-names></name><xref ref-type="aff" rid="A13">13</xref></contrib><contrib contrib-type="author"><name><surname>Eeles</surname><given-names>Rosalind A</given-names></name><xref ref-type="aff" rid="A13">13</xref><xref ref-type="aff" rid="A14">14</xref></contrib><contrib contrib-type="author"><collab>for the UKGPCS Collaborators</collab><xref ref-type="aff" rid="A13">13</xref></contrib><contrib contrib-type="author"><name><surname>Hopper</surname><given-names>John L.</given-names></name><xref ref-type="aff" rid="A2">2</xref><xref ref-type="aff" rid="A15">15</xref></contrib><contrib contrib-type="author"><name><surname>Giles</surname><given-names>Graham G.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref ref-type="aff" rid="A2">2</xref></contrib></contrib-group><aff id="A1"><label>1</label>Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia</aff><aff id="A2"><label>2</label>Centre For Epidemiology and Biostatistics, University of Melbourne, Melbourne, Australia</aff><aff id="A3"><label>3</label>Human Genetics Foundation, Torino, Italy; Université Paris-Saclay, Univ. Paris-Sud, UVSQ, CESP, INSERM, Villejuif, France; Gustave Roussy, F-94805, Villejuif, France</aff><aff id="A4"><label>4</label>Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania</aff><aff id="A5"><label>5</label>IBM Research - Zurich, Switzerland</aff><aff id="A6"><label>6</label>UNU-MERIT (United Nations University – Maastricht Economic and Social Research Institute on Innovation and Technology) Maastricht University, Maastricht, The Netherlands</aff><aff id="A7"><label>7</label>Warsaw University of Technology, Warsaw, Poland</aff><aff id="A8"><label>8</label>School of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia</aff><aff id="A9"><label>9</label>IBM Research – Australia, Carlton, Australia</aff><aff id="A10"><label>10</label>Genetic Epidemiology Laboratory, Department of Pathology, University of Melbourne, VIC, Australia</aff><aff id="A11"><label>11</label>Melbourne Bioinformatics Platform, Victorian Life Sciences Computation Initiative, University of Melbourne, VIC, Australia</aff><aff id="A12"><label>12</label>Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, UK</aff><aff id="A13"><label>13</label>The Institute of Cancer Research, London, UK</aff><aff id="A14"><label>14</label>The Royal Marsden NHS Foundation Trust, Surrey, UK</aff><aff id="A15"><label>15</label>Department of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea</aff><author-notes><corresp id="FN1">Author for correspondence: Professor John L. Hopper, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, 207 Bouverie Street, Carlton, Victoria 3053, Australia, Tel: 61-3-8344-0697, Fax: 61-3-9349-5815, <email>j.hopper@unimelb.edu.au</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>21</day><month>12</month><year>2016</year></pub-date><pub-date pub-type="epub"><day>18</day><month>8</month><year>2016</year></pub-date><pub-date pub-type="ppub"><month>12</month><year>2016</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>6</month><year>2017</year></pub-date><volume>25</volume><issue>12</issue><fpage>1619</fpage><lpage>1624</lpage><pmc-comment>elocation-id from pubmed: 10.1158/1055-9965.EPI-16-0301</pmc-comment>
<abstract><sec id="S1"><title>Background</title><p id="P1">We have developed a GWAS analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of contiguous markers (e.g. single nucleotide polymorphisms, SNPs) across the genome. DEPTH is a machine learning algorithm for feature ranking of ultra-high dimensional datasets, built from well-established statistical tools such as bootstrapping, penalised regression and decision trees. Unlike marginal regression, which considers each SNP individually, the key idea behind DEPTH is to rank groups of SNPs in terms of their joint strength of association with the outcome. Our aim was to compare the performance of DEPTH with that of standard logistic regression analysis.</p></sec><sec id="S2"><title>Methods</title><p id="P2">We selected 1,854 prostate cancer cases and 1,894 controls from the UK for whom 541,129 SNPs were measured using the Illumina Infinium HumanHap550 array. Confirmation was sought using 4,152 cases and 2,874 controls, ascertained from the UK and Australia, for whom 211,155 SNPs were measured using the iCOGS Illumina Infinium array.</p></sec><sec id="S3"><title>Results</title><p id="P3">From the DEPTH analysis we identified 14 regions associated with prostate cancer risk that had been reported previously; five of which would not have been identified by conventional logistic regression. We also identified 112 novel putative susceptibility regions.</p></sec><sec id="S4"><title>Conclusions</title><p id="P4">DEPTH can reveal new risk-associated regions that would not have been identified using a conventional logistic regression analysis of individual SNPs.</p></sec><sec id="S5"><title>Impact</title><p id="P5">This study demonstrates that the DEPTH algorithm could identify additional genetic susceptibility regions that merit further investigation.</p></sec></abstract><kwd-group><kwd>genome-wide association studies</kwd><kwd>machine learning algorithm</kwd><kwd>decision trees</kwd><kwd>single nucleotide polymorphism</kwd><kwd>prostate cancer</kwd></kwd-group></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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| This area was generated with Dilib version V0.6.33. |  |