An evaluation of power and type I error of single-nucleotide polymorphism transmission/disequilibrium-based statistical methods under different family structures, missing parental data, and population stratification

Kristin K Nicodemus, Augustin Luna, Yin Yao Shugart

Research output: Contribution to journalArticlepeer-review

Abstract

Researchers conducting family-based association studies have a wide variety of transmission/disequilibrium (TD)-based methods to choose from, but few guidelines exist in the selection of a particular method to apply to available data. Using a simulation study design, we compared the power and type I error of eight popular TD-based methods under different family structures, frequencies of missing parental data, genetic models, and population stratifications. No method was uniformly most powerful under all conditions, but type I error was appropriate for nearly every test statistic under all conditions. Power varied widely across methods, with a 46.5% difference in power observed between the most powerful and the least powerful method when 50% of families consisted of an affected sib pair and one parent genotyped under an additive genetic model and a 35.2% difference when 50% of families consisted of a single affection-discordant sibling pair without parental genotypes available under an additive genetic model. Methods were generally robust to population stratification, although some slightly less so than others. The choice of a TD-based test statistic should be dependent on the predominant family structure ascertained, the frequency of missing parental genotypes, and the assumed genetic model.

Original languageEnglish
Pages (from-to)178-85
Number of pages8
JournalAmerican Journal of Human Genetics
Volume80
Issue number1
DOIs
Publication statusPublished - Jan 2007

Keywords

  • Computer Simulation
  • Genotype
  • Humans
  • Linkage Disequilibrium
  • Models, Genetic
  • Parents
  • Polymorphism, Single Nucleotide
  • Population Groups
  • Software
  • Statistics as Topic
  • Comparative Study
  • Journal Article
  • Research Support, N.I.H., Extramural

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