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Genotype‐Based Association Analysis Using Discordant Pairs: A Penetrance Odds Ratio Approach
Summary Genotypic counts of paired relatives discordant for a complex late‐onset disease are often used to test for genetic association. The power of the various statistical test options, when data on covariates are unavailable, has been the focus of recent research. Comparison of the Cochran‐Armita...
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Published in: | Annals of human genetics 2013-03, Vol.77 (2), p.137-146 |
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container_title | Annals of human genetics |
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creator | Grover, Vaneeta K. Cole, David E.C. Hamilton, David C. |
description | Summary
Genotypic counts of paired relatives discordant for a complex late‐onset disease are often used to test for genetic association. The power of the various statistical test options, when data on covariates are unavailable, has been the focus of recent research. Comparison of the Cochran‐Armitage, Bhapkar, and McNemar tests indicates that none is superior to the others in all cases. Using an alternative approach, we found that the theoretical genotypic frequencies of the discordant pairs depend only on the penetrance odds ratios, after conditioning. These odds ratios can be estimated by maximizing a product binomial likelihood and provide insight into the mode of inheritance. We identified cases where exact maximum likelihood (ML) estimates can be explicitly obtained. This approach led us to two tests for association which depend on likelihood ratio (LR) or score statistics. We quantified the power of these tests analytically and examined their performance through simulation. We explored the utility of these tests with an example from the literature—the association between complement factor H (CFH) polymorphisms and age‐related macular degeneration. The LR and Score tests serve as simple and effective ways of interpreting paired case‐control data sets. |
doi_str_mv | 10.1111/ahg.12002 |
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Genotypic counts of paired relatives discordant for a complex late‐onset disease are often used to test for genetic association. The power of the various statistical test options, when data on covariates are unavailable, has been the focus of recent research. Comparison of the Cochran‐Armitage, Bhapkar, and McNemar tests indicates that none is superior to the others in all cases. Using an alternative approach, we found that the theoretical genotypic frequencies of the discordant pairs depend only on the penetrance odds ratios, after conditioning. These odds ratios can be estimated by maximizing a product binomial likelihood and provide insight into the mode of inheritance. We identified cases where exact maximum likelihood (ML) estimates can be explicitly obtained. This approach led us to two tests for association which depend on likelihood ratio (LR) or score statistics. We quantified the power of these tests analytically and examined their performance through simulation. We explored the utility of these tests with an example from the literature—the association between complement factor H (CFH) polymorphisms and age‐related macular degeneration. The LR and Score tests serve as simple and effective ways of interpreting paired case‐control data sets.</description><identifier>ISSN: 0003-4800</identifier><identifier>EISSN: 1469-1809</identifier><identifier>DOI: 10.1111/ahg.12002</identifier><identifier>PMID: 23362881</identifier><identifier>CODEN: ANHGAA</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Case-Control Studies ; discordant relative pairs ; Genetic association ; Genetic Association Studies - methods ; Genotype ; Genotype & phenotype ; Humans ; Macular degeneration ; Odds Ratio ; odds ratios ; Penetrance ; Polymorphism, Single Nucleotide ; Studies</subject><ispartof>Annals of human genetics, 2013-03, Vol.77 (2), p.137-146</ispartof><rights>2013 Blackwell Publishing Ltd/University College London</rights><rights>2013 Blackwell Publishing Ltd/University College London.</rights><rights>Annals of Human Genetics © 2013 Blackwell Publishing Ltd/University College London</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3462-535d75a3aaf3f10516895b4327aaee6c9916086e2a7a68bef8ffaf889fc7f3e83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23362881$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Grover, Vaneeta K.</creatorcontrib><creatorcontrib>Cole, David E.C.</creatorcontrib><creatorcontrib>Hamilton, David C.</creatorcontrib><title>Genotype‐Based Association Analysis Using Discordant Pairs: A Penetrance Odds Ratio Approach</title><title>Annals of human genetics</title><addtitle>Ann Hum Genet</addtitle><description>Summary
Genotypic counts of paired relatives discordant for a complex late‐onset disease are often used to test for genetic association. The power of the various statistical test options, when data on covariates are unavailable, has been the focus of recent research. Comparison of the Cochran‐Armitage, Bhapkar, and McNemar tests indicates that none is superior to the others in all cases. Using an alternative approach, we found that the theoretical genotypic frequencies of the discordant pairs depend only on the penetrance odds ratios, after conditioning. These odds ratios can be estimated by maximizing a product binomial likelihood and provide insight into the mode of inheritance. We identified cases where exact maximum likelihood (ML) estimates can be explicitly obtained. This approach led us to two tests for association which depend on likelihood ratio (LR) or score statistics. We quantified the power of these tests analytically and examined their performance through simulation. We explored the utility of these tests with an example from the literature—the association between complement factor H (CFH) polymorphisms and age‐related macular degeneration. The LR and Score tests serve as simple and effective ways of interpreting paired case‐control data sets.</description><subject>Case-Control Studies</subject><subject>discordant relative pairs</subject><subject>Genetic association</subject><subject>Genetic Association Studies - methods</subject><subject>Genotype</subject><subject>Genotype & phenotype</subject><subject>Humans</subject><subject>Macular degeneration</subject><subject>Odds Ratio</subject><subject>odds ratios</subject><subject>Penetrance</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Studies</subject><issn>0003-4800</issn><issn>1469-1809</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNqF0btOwzAUBmALgaBcBl4AWWKBIdSXxHHYwq0gIbVCdCU6TY5LUJoUOxXqxiPwjDwJhhQGJIQXL9_5bZ2fkH3OTrg_fXicnnDBmFgjPR6qJOCaJeukxxiTQagZ2yLbzj0xxoUO5SbZElIqoTXvkYcB1k27nOP769sZOCxo6lyTl9CWTU3TGqqlKx0du7Ke0ovS5Y0toG7pCErrTmlKR1hja6HOkQ6LwtG7z0mazue2gfxxl2wYqBzure4dMr66vD-_Dm6Hg5vz9DbIZahEEMmoiCOQAEYaziKudBJNQiliAESVJwlXTCsUEIPSEzTaGDBaJyaPjUQtd8hRl-uffV6ga7OZ_ytWFdTYLFzGJY-U8KuQ_1OhkzBWHT38RZ-ahfU7-VI6CmMpI6-OO5XbxjmLJpvbcgZ2mXGWffaT-X6yr368PVglLiYzLH7kdyEe9DvwUla4_DspS68HXeQHCTyYxQ</recordid><startdate>201303</startdate><enddate>201303</enddate><creator>Grover, Vaneeta K.</creator><creator>Cole, David E.C.</creator><creator>Hamilton, David C.</creator><general>Wiley Subscription Services, Inc</general><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>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>201303</creationdate><title>Genotype‐Based Association Analysis Using Discordant Pairs: A Penetrance Odds Ratio Approach</title><author>Grover, Vaneeta K. ; Cole, David E.C. ; Hamilton, David C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3462-535d75a3aaf3f10516895b4327aaee6c9916086e2a7a68bef8ffaf889fc7f3e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Case-Control Studies</topic><topic>discordant relative pairs</topic><topic>Genetic association</topic><topic>Genetic Association Studies - methods</topic><topic>Genotype</topic><topic>Genotype & phenotype</topic><topic>Humans</topic><topic>Macular degeneration</topic><topic>Odds Ratio</topic><topic>odds ratios</topic><topic>Penetrance</topic><topic>Polymorphism, Single Nucleotide</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Grover, Vaneeta K.</creatorcontrib><creatorcontrib>Cole, David E.C.</creatorcontrib><creatorcontrib>Hamilton, David C.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Annals of human genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Grover, Vaneeta K.</au><au>Cole, David E.C.</au><au>Hamilton, David C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genotype‐Based Association Analysis Using Discordant Pairs: A Penetrance Odds Ratio Approach</atitle><jtitle>Annals of human genetics</jtitle><addtitle>Ann Hum Genet</addtitle><date>2013-03</date><risdate>2013</risdate><volume>77</volume><issue>2</issue><spage>137</spage><epage>146</epage><pages>137-146</pages><issn>0003-4800</issn><eissn>1469-1809</eissn><coden>ANHGAA</coden><abstract>Summary
Genotypic counts of paired relatives discordant for a complex late‐onset disease are often used to test for genetic association. The power of the various statistical test options, when data on covariates are unavailable, has been the focus of recent research. Comparison of the Cochran‐Armitage, Bhapkar, and McNemar tests indicates that none is superior to the others in all cases. Using an alternative approach, we found that the theoretical genotypic frequencies of the discordant pairs depend only on the penetrance odds ratios, after conditioning. These odds ratios can be estimated by maximizing a product binomial likelihood and provide insight into the mode of inheritance. We identified cases where exact maximum likelihood (ML) estimates can be explicitly obtained. This approach led us to two tests for association which depend on likelihood ratio (LR) or score statistics. We quantified the power of these tests analytically and examined their performance through simulation. We explored the utility of these tests with an example from the literature—the association between complement factor H (CFH) polymorphisms and age‐related macular degeneration. The LR and Score tests serve as simple and effective ways of interpreting paired case‐control data sets.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>23362881</pmid><doi>10.1111/ahg.12002</doi><tpages>10</tpages></addata></record> |
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subjects | Case-Control Studies discordant relative pairs Genetic association Genetic Association Studies - methods Genotype Genotype & phenotype Humans Macular degeneration Odds Ratio odds ratios Penetrance Polymorphism, Single Nucleotide Studies |
title | Genotype‐Based Association Analysis Using Discordant Pairs: A Penetrance Odds Ratio Approach |
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