X‐LRT: a likelihood approach to estimate genetic risks and test association with X‐linked markers using a case‐parents design
Identifieur interne : 001C87 ( Main/Corpus ); précédent : 001C86; suivant : 001C88X‐LRT: a likelihood approach to estimate genetic risks and test association with X‐linked markers using a case‐parents design
Auteurs : Li Zhang ; Eden R. Martin ; Ren-Hua Chung ; Yi-Ju Li ; Richard W. MorrisSource :
- Genetic Epidemiology [ 0741-0395 ] ; 2008-05.
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Abstract
Recently, there has been interest in family‐based tests of association to identify X‐chromosome genes. However, none of the approaches allow for estimation of genetic risks. We propose a likelihood approach to estimate disease‐related marker relative risks and test genotype association using a case‐parents design. The test uses nuclear families with a single affected proband and allows additional siblings and missing parental genotypes. Extension to a haplotype test is based on assumptions of random mating and multiplicative penetrance. We investigate power and type I error rate of the likelihood‐based test, using simulated data and apply our method to marker data from the monoamine oxidase A&B genes in families with Parkinson disease. We show how efficiency with missing parental information can be improved with additional sibling genotype information. Our likelihood approach offers great flexibility for testing different penetrance relationships within and between sexes. In addition, estimation of disease‐related marker relative risks provides a measure of the magnitude of X‐linked genetic effects on complex disorders. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.
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DOI: 10.1002/gepi.20311
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Martin</name><affiliation><mods:affiliation>Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida</mods:affiliation></affiliation></author><author><name sortKey="Chung, Ren Ua" sort="Chung, Ren Ua" uniqKey="Chung R" first="Ren-Hua" last="Chung">Ren-Hua Chung</name><affiliation><mods:affiliation>Center for Human Genetics, Duke University Medical Center, Durham, North Carolina</mods:affiliation></affiliation></author><author><name sortKey="Li, Yi U" sort="Li, Yi U" uniqKey="Li Y" first="Yi-Ju" last="Li">Yi-Ju Li</name><affiliation><mods:affiliation>Center for Human Genetics, Duke University Medical Center, Durham, North Carolina</mods:affiliation></affiliation></author><author><name sortKey="Morris, Richard W" sort="Morris, Richard W" uniqKey="Morris R" first="Richard W." last="Morris">Richard W. 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However, none of the approaches allow for estimation of genetic risks. We propose a likelihood approach to estimate disease‐related marker relative risks and test genotype association using a case‐parents design. The test uses nuclear families with a single affected proband and allows additional siblings and missing parental genotypes. Extension to a haplotype test is based on assumptions of random mating and multiplicative penetrance. We investigate power and type I error rate of the likelihood‐based test, using simulated data and apply our method to marker data from the monoamine oxidase A&B genes in families with Parkinson disease. We show how efficiency with missing parental information can be improved with additional sibling genotype information. Our likelihood approach offers great flexibility for testing different penetrance relationships within and between sexes. In addition, estimation of disease‐related marker relative risks provides a measure of the magnitude of X‐linked genetic effects on complex disorders. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Li Zhang</name><affiliations><json:string>Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina</json:string><json:string>Center for Human Genetics, Duke University Medical Center, Durham, North Carolina</json:string></affiliations></json:item><json:item><name>Eden R. 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However, none of the approaches allow for estimation of genetic risks. We propose a likelihood approach to estimate disease‐related marker relative risks and test genotype association using a case‐parents design. The test uses nuclear families with a single affected proband and allows additional siblings and missing parental genotypes. Extension to a haplotype test is based on assumptions of random mating and multiplicative penetrance. We investigate power and type I error rate of the likelihood‐based test, using simulated data and apply our method to marker data from the monoamine oxidase A&B genes in families with Parkinson disease. We show how efficiency with missing parental information can be improved with additional sibling genotype information. Our likelihood approach offers great flexibility for testing different penetrance relationships within and between sexes. In addition, estimation of disease‐related marker relative risks provides a measure of the magnitude of X‐linked genetic effects on complex disorders. <i>Genet. Epidemiol</i>. 2008. © 2008 Wiley‐Liss, Inc.</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>X‐LRT: a likelihood approach to estimate genetic risks and test association with X‐linked markers using a case‐parents design</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>X‐LRT: A Likelihood Approach</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>X‐LRT: a likelihood approach to estimate genetic risks and test association with X‐linked markers using a case‐parents design</title></titleInfo><name type="personal"><namePart type="given">Li</namePart><namePart type="family">Zhang</namePart><affiliation>Bioinformatics Research Center, North Carolina State University, Raleigh, North Carolina</affiliation><affiliation>Center for Human Genetics, Duke University Medical Center, Durham, North Carolina</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Eden R.</namePart><namePart type="family">Martin</namePart><affiliation>Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Ren‐Hua</namePart><namePart type="family">Chung</namePart><affiliation>Center for Human Genetics, Duke University Medical Center, Durham, North Carolina</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yi‐Ju</namePart><namePart type="family">Li</namePart><affiliation>Center for Human Genetics, Duke University Medical Center, Durham, North Carolina</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Richard W.</namePart><namePart type="family">Morris</namePart><affiliation>Miami Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida</affiliation><description>Correspondence: Miami Institute for Human Genomics, University of Miami, Miller School of Medicine, 1120 NW 14th Street, CRB‐838 (M860), Miami, FL 33136===</description><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><place><placeTerm type="text">Hoboken</placeTerm></place><dateIssued encoding="w3cdtf">2008-05</dateIssued><dateCaptured encoding="w3cdtf">2007-04-24</dateCaptured><dateValid encoding="w3cdtf">2007-12-20</dateValid><copyrightDate encoding="w3cdtf">2008</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">2</extent><extent unit="tables">6</extent><extent unit="references">23</extent></physicalDescription><abstract lang="en">Recently, there has been interest in family‐based tests of association to identify X‐chromosome genes. However, none of the approaches allow for estimation of genetic risks. We propose a likelihood approach to estimate disease‐related marker relative risks and test genotype association using a case‐parents design. The test uses nuclear families with a single affected proband and allows additional siblings and missing parental genotypes. Extension to a haplotype test is based on assumptions of random mating and multiplicative penetrance. We investigate power and type I error rate of the likelihood‐based test, using simulated data and apply our method to marker data from the monoamine oxidase A&B genes in families with Parkinson disease. We show how efficiency with missing parental information can be improved with additional sibling genotype information. Our likelihood approach offers great flexibility for testing different penetrance relationships within and between sexes. In addition, estimation of disease‐related marker relative risks provides a measure of the magnitude of X‐linked genetic effects on complex disorders. Genet. Epidemiol. 2008. © 2008 Wiley‐Liss, Inc.</abstract><note type="funding">NIH - No. NS051355; No. NS39764; </note><subject lang="en"><genre>Keywords</genre><topic>sex linked</topic><topic>maximum‐likelihood estimation</topic><topic>confidence interval</topic><topic>hypothesis test</topic><topic>family‐based design</topic></subject><relatedItem type="host"><titleInfo><title>Genetic Epidemiology</title><subTitle>The Official Publication of the International Genetic Epidemiology Society</subTitle></titleInfo><titleInfo type="abbreviated"><title>Genet. Epidemiol.</title></titleInfo><genre type="Journal">journal</genre><subject><genre>article category</genre><topic>Original Article</topic></subject><identifier type="ISSN">0741-0395</identifier><identifier type="eISSN">1098-2272</identifier><identifier type="DOI">10.1002/(ISSN)1098-2272</identifier><identifier type="PublisherID">GEPI</identifier><part><date>2008</date><detail type="volume"><caption>vol.</caption><number>32</number></detail><detail type="issue"><caption>no.</caption><number>4</number></detail><extent unit="pages"><start>370</start><end>380</end><total>11</total></extent></part></relatedItem><identifier type="istex">213F6FBA48C1D020DAC54904334A3E2CB04024A7</identifier><identifier type="DOI">10.1002/gepi.20311</identifier><identifier type="ArticleID">GEPI20311</identifier><accessCondition type="use and reproduction" contentType="copyright">© 2008 Wiley‐Liss, Inc.</accessCondition><recordInfo><recordContentSource>WILEY</recordContentSource><recordOrigin>Wiley Subscription Services, Inc., A Wiley Company</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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