Heritability estimation of dichotomous phenotypes using a liability threshold model on ascertained family‐based samples
Numerous methods for estimating heritability have been proposed; however, unlike quantitative phenotypes, heritability estimation for dichotomous phenotypes is computationally and statistically complex, and the use of heritability is infrequent. In this study, we developed a statistical method to es...
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Veröffentlicht in: | Genetic epidemiology 2019-10, Vol.43 (7), p.761-775 |
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creator | Kim, Wonji Kwak, Soo Heon Won, Sungho |
description | Numerous methods for estimating heritability have been proposed; however, unlike quantitative phenotypes, heritability estimation for dichotomous phenotypes is computationally and statistically complex, and the use of heritability is infrequent. In this study, we developed a statistical method to estimate heritability of dichotomous phenotypes using a liability threshold model in the context of ascertained family‐based samples. This model assumes that dichotomous phenotypes are determined by unobserved latent variables that are normally distributed and can be applied to general pedigree data. The proposed methods were applied to simulated data and Korean type‐2 diabetes family‐based samples, and the accuracy of the estimates provided by the experimental methods was compared with that of the established methods. |
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The proposed methods were applied to simulated data and Korean type‐2 diabetes family‐based samples, and the accuracy of the estimates provided by the experimental methods was compared with that of the established methods.</description><identifier>ISSN: 0741-0395</identifier><identifier>EISSN: 1098-2272</identifier><identifier>DOI: 10.1002/gepi.22244</identifier><identifier>PMID: 31298783</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Adult ; Algorithms ; ascertainment bias ; Computer Simulation ; Diabetes mellitus ; Diabetes Mellitus, Type 2 - genetics ; Family ; Female ; Genetic Predisposition to Disease ; Heritability ; Humans ; Inheritance Patterns - genetics ; liability threshold model ; Male ; Middle Aged ; Models, Genetic ; Pedigree ; Phenotype ; Phenotypes ; Risk Factors</subject><ispartof>Genetic epidemiology, 2019-10, Vol.43 (7), p.761-775</ispartof><rights>2019 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3574-97cd9f4f770507433214cefa189c99a2a95c782bda0879a1edac277536587a2b3</citedby><cites>FETCH-LOGICAL-c3574-97cd9f4f770507433214cefa189c99a2a95c782bda0879a1edac277536587a2b3</cites><orcidid>0000-0002-1249-797X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fgepi.22244$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fgepi.22244$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,27922,27923,45572,45573</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31298783$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kim, Wonji</creatorcontrib><creatorcontrib>Kwak, Soo Heon</creatorcontrib><creatorcontrib>Won, Sungho</creatorcontrib><title>Heritability estimation of dichotomous phenotypes using a liability threshold model on ascertained family‐based samples</title><title>Genetic epidemiology</title><addtitle>Genet Epidemiol</addtitle><description>Numerous methods for estimating heritability have been proposed; however, unlike quantitative phenotypes, heritability estimation for dichotomous phenotypes is computationally and statistically complex, and the use of heritability is infrequent. In this study, we developed a statistical method to estimate heritability of dichotomous phenotypes using a liability threshold model in the context of ascertained family‐based samples. This model assumes that dichotomous phenotypes are determined by unobserved latent variables that are normally distributed and can be applied to general pedigree data. The proposed methods were applied to simulated data and Korean type‐2 diabetes family‐based samples, and the accuracy of the estimates provided by the experimental methods was compared with that of the established methods.</description><subject>Adult</subject><subject>Algorithms</subject><subject>ascertainment bias</subject><subject>Computer Simulation</subject><subject>Diabetes mellitus</subject><subject>Diabetes Mellitus, Type 2 - genetics</subject><subject>Family</subject><subject>Female</subject><subject>Genetic Predisposition to Disease</subject><subject>Heritability</subject><subject>Humans</subject><subject>Inheritance Patterns - genetics</subject><subject>liability threshold model</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Models, Genetic</subject><subject>Pedigree</subject><subject>Phenotype</subject><subject>Phenotypes</subject><subject>Risk Factors</subject><issn>0741-0395</issn><issn>1098-2272</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kctq3TAQhkVpaU5Pu-kDFEE3oeBUF6uyliHkBoFmka7NWB7nKMiWI9kE7_IIecY8SXRyki6yyEoIvvmYf35CvnN2wBkTv69xdAdCiLL8QFacmaoQQouPZMV0yQsmjdojX1K6YYzz0qjPZE9yYSpdyRVZzjC6CRrn3bRQTJPrYXJhoKGjrbObMIU-zImOGxzCtIyY6JzccE2Bevc6Nm0ipk3wLe1Di57mcUgW4wRuwJZ20Du_PN4_NJDyN0E_ekxfyacOfMJvL--a_Ds5vjo6Ky7-np4fHV4UVipdFkbb1nRlpzVTOY-UgpcWO-CVscaAAKOsrkTTAqu0AY4tWKG1kn9UpUE0ck32d94xhts5J6x7l5fzHgbMyWohVHaz7TnW5Ocb9CbMccjbZcporirJeaZ-7SgbQ0oRu3qM-WpxqTmrt4XU20Lq50Iy_ONFOTc9tv_R1wYywHfAnfO4vKOqT48vz3fSJ_67mHM</recordid><startdate>201910</startdate><enddate>201910</enddate><creator>Kim, Wonji</creator><creator>Kwak, Soo Heon</creator><creator>Won, Sungho</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>7QP</scope><scope>7QR</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-1249-797X</orcidid></search><sort><creationdate>201910</creationdate><title>Heritability estimation of dichotomous phenotypes using a liability threshold model on ascertained family‐based samples</title><author>Kim, Wonji ; Kwak, Soo Heon ; Won, Sungho</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3574-97cd9f4f770507433214cefa189c99a2a95c782bda0879a1edac277536587a2b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Algorithms</topic><topic>ascertainment bias</topic><topic>Computer Simulation</topic><topic>Diabetes mellitus</topic><topic>Diabetes Mellitus, Type 2 - genetics</topic><topic>Family</topic><topic>Female</topic><topic>Genetic Predisposition to Disease</topic><topic>Heritability</topic><topic>Humans</topic><topic>Inheritance Patterns - genetics</topic><topic>liability threshold model</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Models, Genetic</topic><topic>Pedigree</topic><topic>Phenotype</topic><topic>Phenotypes</topic><topic>Risk Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Wonji</creatorcontrib><creatorcontrib>Kwak, Soo Heon</creatorcontrib><creatorcontrib>Won, Sungho</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Genetic epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Wonji</au><au>Kwak, Soo Heon</au><au>Won, Sungho</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Heritability estimation of dichotomous phenotypes using a liability threshold model on ascertained family‐based samples</atitle><jtitle>Genetic epidemiology</jtitle><addtitle>Genet Epidemiol</addtitle><date>2019-10</date><risdate>2019</risdate><volume>43</volume><issue>7</issue><spage>761</spage><epage>775</epage><pages>761-775</pages><issn>0741-0395</issn><eissn>1098-2272</eissn><abstract>Numerous methods for estimating heritability have been proposed; however, unlike quantitative phenotypes, heritability estimation for dichotomous phenotypes is computationally and statistically complex, and the use of heritability is infrequent. In this study, we developed a statistical method to estimate heritability of dichotomous phenotypes using a liability threshold model in the context of ascertained family‐based samples. This model assumes that dichotomous phenotypes are determined by unobserved latent variables that are normally distributed and can be applied to general pedigree data. The proposed methods were applied to simulated data and Korean type‐2 diabetes family‐based samples, and the accuracy of the estimates provided by the experimental methods was compared with that of the established methods.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>31298783</pmid><doi>10.1002/gepi.22244</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-1249-797X</orcidid></addata></record> |
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subjects | Adult Algorithms ascertainment bias Computer Simulation Diabetes mellitus Diabetes Mellitus, Type 2 - genetics Family Female Genetic Predisposition to Disease Heritability Humans Inheritance Patterns - genetics liability threshold model Male Middle Aged Models, Genetic Pedigree Phenotype Phenotypes Risk Factors |
title | Heritability estimation of dichotomous phenotypes using a liability threshold model on ascertained family‐based samples |
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