Power for complex trait genetic association

Derek Gordon, Francisco M. De La Vega, Stephen J. Finch, Qian K. Ye

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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
Volume5
Issue number1 SPEC. ISS.
DOIs
StatePublished - Sep 2005

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Genes
Genetic Models
Schizophrenia
Research Personnel
Power (Psychology)

Keywords

  • Association mapping
  • Linkage disequilibrium mapping
  • Single nucleotide polymorphism

ASJC Scopus subject areas

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

Cite this

Power for complex trait genetic association. / Gordon, Derek; De La Vega, Francisco M.; Finch, Stephen J.; Ye, Qian K.

In: Clinical Neuroscience Research, Vol. 5, No. 1 SPEC. ISS., 09.2005, p. 31-35.

Research output: Contribution to journalArticle

Gordon, D, De La Vega, FM, Finch, SJ & Ye, QK 2005, 'Power for complex trait genetic association', Clinical Neuroscience Research, vol. 5, no. 1 SPEC. ISS., pp. 31-35. https://doi.org/10.1016/j.cnr.2005.07.004
Gordon, Derek ; De La Vega, Francisco M. ; Finch, Stephen J. ; Ye, Qian K. / Power for complex trait genetic association. In: Clinical Neuroscience Research. 2005 ; Vol. 5, No. 1 SPEC. ISS. pp. 31-35.
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