title: Association analysis of complex diseases using triads, parent-child dyads and singleton monads.
abstract: BACKGROUND
  Triad families are routinely used to test association between genetic variants and complex diseases. Triad studies are important and popular since they are robust in terms of being less prone to false positives due to population structure. In practice, one may collect not only complete triads, but also incomplete families such as dyads (affected child with one parent) and singleton monads (affected child without parents). Since there is a lack of convenient algorithms and software to analyze the incomplete data, dyads and monads are usually discarded. This may lead to loss of power and insufficient utilization of genetic information in a study.
  
  
  RESULTS
  We develop likelihood-based statistical models and likelihood ratio tests to test for association between complex diseases and genetic markers by using combinations of full triads, parent-child dyads, and affected singleton monads for a unified analysis. A likelihood is calculated directly to facilitate the data analysis without imputation and to avoid computational complexity. This makes it easy to implement the models and to explain the results.
  
  
  CONCLUSIONS
  By simulation studies, we show that the proposed models and tests are very robust in terms of accurately controlling type I error evaluations, and are powerful by empirical power evaluations. The methods are applied to test for association between transforming growth factor alpha (TGFA) gene and cleft palate in an Irish study.
authors.affiliation: Biostatistics and Bioinformatics Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, 6100 Executive Blvd, MSC 7510, Rockville, MD 20852, USA. fanr@mail.nih.gov.
authors.forename: Ruzong
authors.initials: R
authors.lastname: Fan
authors.forename: Annie
authors.initials: A
authors.lastname: Lee
authors.forename: Zhaohui
authors.initials: Z
authors.lastname: Lu
authors.forename: Aiyi
authors.initials: A
authors.lastname: Liu
authors.forename: James F
authors.initials: JF
authors.lastname: Troendle
authors.forename: James L
authors.initials: JL
authors.lastname: Mills
mesh_terms: D000465:Algorithms; D000483:Alleles; D002648:Child; D002972:Cleft Palate / Q000235:genetics; D004194:Disease / Q000235:genetics*; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide; D012984:Software; D016211:Transforming Growth Factor alpha / Q000235:genetics
chemical_list: D016211:Transforming Growth Factor alpha