New joint covariance- and marginal-based tests for association and linkage for quantitative traits for random and non-random sampling

Hemant K. Tiwari, Janet Holt, Varghese George, T. Mark Beasley, Christopher I. Amos, David B. Allison

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We develop novel statistical tests for transmission disequilibrium testing (tests of linkage in the presence of association) for quantitative traits using parents and offspring. These joint tests utilize information in both the covariance (or more generally, dependency) between genotype and phenotype and the marginal distribution of genotype. Using computer simulation we test the validity (Type I error rate control) and power of the proposed methods, for additive, dominant, and recessive modes of inheritance, locus-specific heritability of the trait 0.05, 0.1, 0.2 with allele frequencies of P=0.2 and 0.4, and sample sizes of 500, 200, and 100 trios. Both random sampling and extreme sampling schemes were investigated. A multinomial logistic joint test provides the highest overall power irrespective of sample size, allele frequency, heritability, and modes of inheritance.

Original languageEnglish (US)
Pages (from-to)48-57
Number of pages10
JournalGenetic Epidemiology
Volume28
Issue number1
DOIs
StatePublished - Jan 2005
Externally publishedYes

Keywords

  • Association
  • Covariance-based tests
  • Extreme sampling
  • Joint-tests
  • Linkage
  • Marginal-based tests
  • QTL
  • TDT

ASJC Scopus subject areas

  • Epidemiology
  • Genetics(clinical)

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