Power for complex trait genetic association

Derek Gordon, Francisco M. De La Vega, Stephen J. Finch, Kenny Q. Ye

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


One of the key issues facing researchers who want to map genes for complex traits is appropriate methodology for statistical power calculations. Most classic methods assume that parameters for the genetic model are known, which is rarely the case for complex traits. Furthermore, few if any methods use empirical data from genes of interest. We present a statistically valid method for performing such power calculations using empirical data and apply it to a candidate gene example for schizophrenia. We also document several advantages of our method, most notably the computation speed with which our power calculations may be performed.

Original languageEnglish (US)
Pages (from-to)31-35
Number of pages5
JournalClinical Neuroscience Research
Issue number1 SPEC. ISS.
StatePublished - Sep 2005


  • Association mapping
  • Linkage disequilibrium mapping
  • Single nucleotide polymorphism

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Neurology
  • Clinical Neurology
  • Psychiatry and Mental health
  • Biological Psychiatry


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