{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T15:10:30Z","timestamp":1772118630086,"version":"3.50.1"},"reference-count":48,"publisher":"Wiley","issue":"5-6","license":[{"start":{"date-parts":[[2022,4,22]],"date-time":"2022-04-22T00:00:00Z","timestamp":1650585600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000052","name":"NIH Office of the Director","doi-asserted-by":"publisher","award":["U24OD023382"],"award-info":[{"award-number":["U24OD023382"]}],"id":[{"id":"10.13039\/100000052","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000072","name":"National Institute of Dental and Craniofacial Research","doi-asserted-by":"publisher","award":["R03DE029254"],"award-info":[{"award-number":["R03DE029254"]}],"id":[{"id":"10.13039\/100000072","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Genetic Epidemiology"],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Genetic association studies of child health outcomes often employ family\u2010based study designs. One of the most popular family\u2010based designs is the case\u2013parent trio design that considers the smallest possible nuclear family consisting of two parents and their affected child. This trio design is particularly advantageous for studying relatively rare disorders because it is less prone to type 1 error inflation due to population stratification compared to population\u2010based study designs (e.g., case\u2013control studies). However, obtaining genetic data from both parents is difficult, from a practical perspective, and many large studies predominantly measure genetic variants in mother\u2013child dyads. While some statistical methods for analyzing parent\u2010child dyad data (most commonly involving mother\u2013child pairs) exist, it is not clear if they provide the same advantage as trio methods in protecting against population stratification, or if a specific dyad design (e.g., case\u2013mother dyads vs. case\u2013mother\/control\u2013mother dyads) is more advantageous. In this article, we review existing statistical methods for analyzing genome\u2010wide marker data on dyads and perform extensive simulation experiments to benchmark their type I errors and statistical power under different scenarios. We extend our evaluation to existing methods for analyzing a combination of case\u2013parent trios and dyads together. We apply these methods on genotyped and imputed data from multiethnic mother\u2013child pairs only, case\u2013parent trios only or combinations of both dyads and trios from the Gene, Environment Association Studies consortium (GENEVA), where each family was ascertained through a child affected by nonsyndromic cleft lip with or without cleft palate. Results from the GENEVA study corroborate the findings from our simulation experiments. Finally, we provide recommendations for using statistical genetic association methods for dyads.<\/jats:p>","DOI":"10.1002\/gepi.22453","type":"journal-article","created":{"date-parts":[[2022,4,22]],"date-time":"2022-04-22T06:05:29Z","timestamp":1650607529000},"page":"266-284","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Benchmarking statistical methods for analyzing parent\u2013child dyads in genetic association studies"],"prefix":"10.1002","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0979-2935","authenticated-orcid":false,"given":"Debashree","family":"Ray","sequence":"first","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"},{"name":"Department of Biostatistics, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Candelaria","family":"Vergara","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Margaret A.","family":"Taub","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Genevieve","family":"Wojcik","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christine","family":"Ladd\u2010Acosta","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Terri H.","family":"Beaty","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Priya","family":"Duggal","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Bloomberg School of Public Health Johns Hopkins University Baltimore Maryland USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,4,22]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/gepi.20547"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.12688\/f1000research.9503.1"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.580"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.2217\/14622416.10.2.181"},{"issue":"7","key":"e_1_2_9_6_1","first-page":"8","article-title":"Second\u2010generation PLINK: rising to the challenge of larger and richer datasets","volume":"4","author":"Chang C. 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