The Merits of Testing Hardy‐Weinberg Equilibrium in the Analysis of Unmatched Case‐Control Data: A Cautionary Note
Summary Testing for departures from the assumption of Hardy‐Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case‐control studies. Some authors suggest using a two‐stage procedure in which gene/disease associations are ultimately evaluated using...
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| Veröffentlicht in: | Annals of human genetics 2006-11, Vol.70 (6), p.923-933 |
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| container_title | Annals of human genetics |
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| creator | Yong Zou, Guang Donner, Allan |
| description | Summary
Testing for departures from the assumption of Hardy‐Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case‐control studies. Some authors suggest using a two‐stage procedure in which gene/disease associations are ultimately evaluated using either the Pearson chi‐square procedure or the Cochran‐Armitage test for trend. Other authors go further and encourage investigators to discard data that are in violation of HWE, essentially using the test as a tool for identifying genotyping errors. In this paper we show that 1) testing for HWE should not be used as a tool to identify genotyping errors; and 2) it is not necessary, and possibly even harmful, to test the HWE assumption before testing for association between alleles and disease. Instead one should inherently account for deviations from HWE with an adjusted chi‐square test statistic, a procedure which in the present context is identical to the trend test. Examples from previous reports are used to illustrate the methodology. |
| doi_str_mv | 10.1111/j.1469-1809.2006.00267.x |
| format | Article |
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Testing for departures from the assumption of Hardy‐Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case‐control studies. Some authors suggest using a two‐stage procedure in which gene/disease associations are ultimately evaluated using either the Pearson chi‐square procedure or the Cochran‐Armitage test for trend. Other authors go further and encourage investigators to discard data that are in violation of HWE, essentially using the test as a tool for identifying genotyping errors. In this paper we show that 1) testing for HWE should not be used as a tool to identify genotyping errors; and 2) it is not necessary, and possibly even harmful, to test the HWE assumption before testing for association between alleles and disease. Instead one should inherently account for deviations from HWE with an adjusted chi‐square test statistic, a procedure which in the present context is identical to the trend test. Examples from previous reports are used to illustrate the methodology.</description><identifier>ISSN: 0003-4800</identifier><identifier>EISSN: 1469-1809</identifier><identifier>DOI: 10.1111/j.1469-1809.2006.00267.x</identifier><identifier>PMID: 17044866</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>adjusted chi‐square ; allelic correlation ; Case-Control Studies ; Chi-Square Distribution ; Cochran‐Mantel‐Haenszel test ; Gene Frequency ; Genotype ; genotyping error ; HuGE ; Humans ; inbreeding coefficient ; Linkage Disequilibrium ; Models, Genetic ; Models, Statistical ; Sample Size ; trend test</subject><ispartof>Annals of human genetics, 2006-11, Vol.70 (6), p.923-933</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3787-df0dfee8f578c7cfa3a9f6ca1c66fd39b27978288a8c8d645c85cbe6a65b801e3</citedby><cites>FETCH-LOGICAL-c3787-df0dfee8f578c7cfa3a9f6ca1c66fd39b27978288a8c8d645c85cbe6a65b801e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1469-1809.2006.00267.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1469-1809.2006.00267.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1416,1432,27922,27923,45572,45573,46407,46831</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/17044866$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yong Zou, Guang</creatorcontrib><creatorcontrib>Donner, Allan</creatorcontrib><title>The Merits of Testing Hardy‐Weinberg Equilibrium in the Analysis of Unmatched Case‐Control Data: A Cautionary Note</title><title>Annals of human genetics</title><addtitle>Ann Hum Genet</addtitle><description>Summary
Testing for departures from the assumption of Hardy‐Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case‐control studies. Some authors suggest using a two‐stage procedure in which gene/disease associations are ultimately evaluated using either the Pearson chi‐square procedure or the Cochran‐Armitage test for trend. Other authors go further and encourage investigators to discard data that are in violation of HWE, essentially using the test as a tool for identifying genotyping errors. In this paper we show that 1) testing for HWE should not be used as a tool to identify genotyping errors; and 2) it is not necessary, and possibly even harmful, to test the HWE assumption before testing for association between alleles and disease. Instead one should inherently account for deviations from HWE with an adjusted chi‐square test statistic, a procedure which in the present context is identical to the trend test. 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Testing for departures from the assumption of Hardy‐Weinberg equilibrium (HWE) has been widely recommended as a preliminary step in the analysis of genetic case‐control studies. Some authors suggest using a two‐stage procedure in which gene/disease associations are ultimately evaluated using either the Pearson chi‐square procedure or the Cochran‐Armitage test for trend. Other authors go further and encourage investigators to discard data that are in violation of HWE, essentially using the test as a tool for identifying genotyping errors. In this paper we show that 1) testing for HWE should not be used as a tool to identify genotyping errors; and 2) it is not necessary, and possibly even harmful, to test the HWE assumption before testing for association between alleles and disease. Instead one should inherently account for deviations from HWE with an adjusted chi‐square test statistic, a procedure which in the present context is identical to the trend test. Examples from previous reports are used to illustrate the methodology.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><pmid>17044866</pmid><doi>10.1111/j.1469-1809.2006.00267.x</doi><tpages>11</tpages></addata></record> |
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| ispartof | Annals of human genetics, 2006-11, Vol.70 (6), p.923-933 |
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| source | MEDLINE; Wiley Free Content; IngentaConnect Free/Open Access Journals; Wiley Online Library All Journals |
| subjects | adjusted chi‐square allelic correlation Case-Control Studies Chi-Square Distribution Cochran‐Mantel‐Haenszel test Gene Frequency Genotype genotyping error HuGE Humans inbreeding coefficient Linkage Disequilibrium Models, Genetic Models, Statistical Sample Size trend test |
| title | The Merits of Testing Hardy‐Weinberg Equilibrium in the Analysis of Unmatched Case‐Control Data: A Cautionary Note |
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