Literature DB >> 17483600

Association analysis of population-based quantitative trait data: an assessment of ANOVA.

Saurabh Ghosh1, Gourab De.   

Abstract

The classical analysis of variance (ANOVA) compares the means of different groups under the assumption that the variances within each of the groups are equal. However, for genetic studies of complex disorders, it is not reasonable to assume that variance of a quantitative trait within each genotype at the trait locus will be equal. Thus, the use of ANOVA may lead to misleading association inferences. In this article, we perform a simulation-based study to assess the rate of false positives and the power of ANOVA under various probability distributions of the quantitative trait and different genetic parameters such as allele frequencies and coefficient of linkage disequilibrium. (c) 2007 S. Karger AG, Basel

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Year:  2007        PMID: 17483600     DOI: 10.1159/000101426

Source DB:  PubMed          Journal:  Hum Hered        ISSN: 0001-5652            Impact factor:   0.444


  4 in total

1.  Effect of population stratification on false positive rates of population-based association analyses of quantitative traits.

Authors:  Tanushree Haldar; Saurabh Ghosh
Journal:  Ann Hum Genet       Date:  2012-05       Impact factor: 1.670

2.  Genome-wide association analyses of quantitative traits: the GAW16 experience.

Authors:  Saurabh Ghosh
Journal:  Genet Epidemiol       Date:  2009       Impact factor: 2.135

3.  Integrating binary traits with quantitative phenotypes for association mapping of multivariate phenotypes.

Authors:  Indranil Mukhopadhyay; Sujayam Saha; Saurabh Ghosh
Journal:  BMC Proc       Date:  2011-11-29

4.  A quantile-based method for association mapping of quantitative phenotypes: an application to rheumatoid arthritis phenotypes.

Authors:  Saurabh Ghosh; Krishna Rao Sanapala; Abhik Ghosh; Sujatro Chakladar
Journal:  BMC Proc       Date:  2009-12-15
  4 in total

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