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Interpretation of simultaneous linkage and family‐based association tests in genome screens

Identifieur interne : 002D01 ( Main/Corpus ); précédent : 002D00; suivant : 002D02

Interpretation of simultaneous linkage and family‐based association tests in genome screens

Auteurs : Ren-Hua Chung ; Elizabeth R. Hauser ; Eden R. Martin

Source :

RBID : ISTEX:E5058DEFF082241487BD41FB9966DFF9E1C290EA

English descriptors

Abstract

Linkage and association analyses have played important roles in identifying susceptibility genes for complex diseases. Linkage tests and family‐based tests of association are often applied in the same data to help fine‐map disease loci or validate results. This paradigm increases efficiency by making maximal use of family data sets. However, it is not intuitively clear under what conditions association and linkage tests performed in the same data set may be correlated. Understanding this relationship is important for interpreting the combined results of both tests. We used computer simulations and theoretical statements to estimate the correlation between linkage statistics (affected sib pair maximum LOD scores) and family‐based association statistics (pedigree disequilibrium test (PDT) and association in the pressure of linkage (APL)) under various hypotheses. Different types of pedigrees were studied: nuclear families with affected sib pairs, extended pedigrees and incomplete pedigrees. Both simulation and theoretical results showed that when there is no linkage or no association, the linkage and association tests are not correlated. When there is linkage and association in the data, the two tests have a positive correlation. We concluded that when linkage and association tests are applied in the same data, the type I error rate of neither test will be affected and that power can be increased by applying tests conditionally. Genet. Epidemiol. © 2006 Wiley‐Liss, Inc.

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DOI: 10.1002/gepi.20196

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ISTEX:E5058DEFF082241487BD41FB9966DFF9E1C290EA

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<dateIssued encoding="w3cdtf">2007-02</dateIssued>
<dateCaptured encoding="w3cdtf">2006-04-14</dateCaptured>
<dateValid encoding="w3cdtf">2006-10-07</dateValid>
<copyrightDate encoding="w3cdtf">2007</copyrightDate>
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<languageTerm type="code" authority="rfc3066">en</languageTerm>
<languageTerm type="code" authority="iso639-2b">eng</languageTerm>
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<extent unit="figures">1</extent>
<extent unit="tables">5</extent>
<extent unit="references">31</extent>
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<abstract lang="en">Linkage and association analyses have played important roles in identifying susceptibility genes for complex diseases. Linkage tests and family‐based tests of association are often applied in the same data to help fine‐map disease loci or validate results. This paradigm increases efficiency by making maximal use of family data sets. However, it is not intuitively clear under what conditions association and linkage tests performed in the same data set may be correlated. Understanding this relationship is important for interpreting the combined results of both tests. We used computer simulations and theoretical statements to estimate the correlation between linkage statistics (affected sib pair maximum LOD scores) and family‐based association statistics (pedigree disequilibrium test (PDT) and association in the pressure of linkage (APL)) under various hypotheses. Different types of pedigrees were studied: nuclear families with affected sib pairs, extended pedigrees and incomplete pedigrees. Both simulation and theoretical results showed that when there is no linkage or no association, the linkage and association tests are not correlated. When there is linkage and association in the data, the two tests have a positive correlation. We concluded that when linkage and association tests are applied in the same data, the type I error rate of neither test will be affected and that power can be increased by applying tests conditionally. Genet. Epidemiol. © 2006 Wiley‐Liss, Inc.</abstract>
<note type="funding">National Institute of Health - No. NS51355; No. MH59528; </note>
<subject lang="en">
<genre>Keywords</genre>
<topic>linkage analysis</topic>
<topic>family‐based association analysis</topic>
<topic>correlation</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>2007</date>
<detail type="volume">
<caption>vol.</caption>
<number>31</number>
</detail>
<detail type="issue">
<caption>no.</caption>
<number>2</number>
</detail>
<extent unit="pages">
<start>134</start>
<end>142</end>
<total>9</total>
</extent>
</part>
</relatedItem>
<identifier type="istex">E5058DEFF082241487BD41FB9966DFF9E1C290EA</identifier>
<identifier type="DOI">10.1002/gepi.20196</identifier>
<identifier type="ArticleID">GEPI20196</identifier>
<accessCondition type="use and reproduction" contentType="copyright">© 2006 Wiley‐Liss, Inc.</accessCondition>
<recordInfo>
<recordContentSource>WILEY</recordContentSource>
<recordOrigin>Wiley Subscription Services, Inc., A Wiley Company</recordOrigin>
</recordInfo>
</mods>
</metadata>
<serie></serie>
</istex>
</record>

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