• Competing analytical strategies of combining associated SNPs for estimating genetic risks

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    • Keywords


      genomewide association study; allele dosage score; regression; variance explained; prediction.

    • Abstract


      In genomewide association study (GWAS) of a complex phenotype, a large number of variants, many with small effect sizes, are found to contribute to the variability of the phenotype. Subsequent to the identification of such variants in a GWAS, it is of interest to estimate the risk jointly conferred by the variants. We propose three different strategies of combining the risk SNPs to calculate an allele dosage score. Using simulations, we evaluate the different measures of allele dosage score with respect to the risk prediction accuracy of a binary trait and the proportion of variance explained for a quantitative trait. For a binary trait, an allele dosage score defined based on log odds ratio performs marginally better than the other two measures. For a quantitative trait, the measure based on the standardized slope coefficient in linear regression of the trait on single-nucleotide polymorphism (SNP) genotypes performs better than the measures using the weights proportional to log P-value and the proportion of variance explained. We demonstrate the utility of these measures using a real dataon type 2 diabetes and fasting blood sugar level in a south Indian population.

    • Author Affiliations



      1. Department of Mathematics, Indian Institute of Technology Hyderabad, Kandi 502 284, India
      2. Human Genetics Unit, Indian Statistical Institute, Kolkata 700 108, India
    • Dates

  • Journal of Genetics | News

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      Posted on July 25, 2019

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