EMK

A novel program for family-based allelic and genotypic association tests on quantitative traits

Y. W. Li, Eden R Martin, Yi Ju Li

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The QTDT program is a widely-used program for analyzing quantitative trait data, but the methods mainly test allelic association. Since the genotype of a marker is a direct observation for an individual, it is of interest to assess association at the genotypic level. In this study, we extended the allele-based association method developed by Monks and Kaplan (MK method) to genotype-based association tests for quantitative traits. We implemented a novel extended MK (EMK) program that can perform both allele- and genotype-based association tests in any pedigree structure. To evaluate the performance of EMK, we utilized simulated pedigree data and real data from our previous report of GSTO1 and GSTO2 genes in Alzheimer disease (AD). Both allele- and genotype-based EMK methods (allele-EMK and geno-EMK) showed correct type I error for various pedigree structures and admixture populations. The geno-EMK method showed comparable power to the allele-EMK test. By treating age-at-onset (AAO) as a quantitative trait, the EMK program was able to detect significant associations for rs4925 in GSTO1 (P = 0.006 for allele-EMK and P = 0.009 for geno-EMK), and rs2297235 in GSTO2 (P = 0.005 for allele-EMK and P = 0.009 for geno-EMK), which are consistent with our previous findings.

Original languageEnglish
Pages (from-to)388-396
Number of pages9
JournalAnnals of Human Genetics
Volume72
Issue number3
DOIs
StatePublished - May 1 2008

Fingerprint

Alleles
Pedigree
Genotype
Age of Onset
Alzheimer Disease
Observation
Population
Genes

Keywords

  • Ageat onset
  • Alzheimer Disease
  • Family-based association
  • Quantitative trait

ASJC Scopus subject areas

  • Genetics(clinical)
  • Genetics

Cite this

EMK : A novel program for family-based allelic and genotypic association tests on quantitative traits. / Li, Y. W.; Martin, Eden R; Li, Yi Ju.

In: Annals of Human Genetics, Vol. 72, No. 3, 01.05.2008, p. 388-396.

Research output: Contribution to journalArticle

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