Journal of Proteomics & Bioinformatics

Journal of Proteomics & Bioinformatics
Open Access

ISSN: 0974-276X

Philip Cooley

Philip Cooley


  • Research Article
    The Influence of Errors Inherent in Genome Wide Association Studies(GWAS) in Relation To Single Gene Models
    Author(s): Philip Cooley, Robert F. Clark and Grier PagePhilip Cooley, Robert F. Clark and Grier Page

    Nearly one thousand human genome wide association studies (GWAS) have examined over 210 diseases and traits and found over 1,200 SNP associations. With improved genotyping technologies and the growing number of available markers, case-control Genome Wide Association Studies (GWAS) have become a key tool for investigating complex diseases. This study assesses the influence of genotype and diagnosis errors present in GWAS by analyzing a synthetic gene dataset incorporating factors known to influence association measurement. Monte Carlo methods were used to generate the synthetic gene data, which incorporated factors including gene inheritance, relative risk levels, disease penetrance, genotype distribution, sample size, as well as the two error factors that are the focus of this study. The resulting dataset provides a truth set for assessing statistical method performance and associatio.. View More»
    DOI: 10.4172/jpb.1000181

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