Gene-based Genomewide Association Analysis: A Comparison Study

Title:Gene-based Genomewide Association Analysis: A Comparison Study

Volume: 14 Issue: 4

Author(s): Guolian Kang, Bo Jiang and Yuehua Cui

Affiliation:

Keywords: Gene-centric, Genome-wide association study, Monte carlo, Entropy, Minimum p-value method.

Abstract: The study of gene-based genetic associations has gained conceptual popularity recently. Biologic insight into the etiology of a complex disease can be gained by focusing on genes as testing units. Several gene-based methods (e.g., minimum p-value (or maximum test statistic) or entropy-based method) have been developed and have more power than a single nucleotide polymorphism (SNP)-based analysis. The objective of this study is to compare the performance of the entropy-based method with the minimum p-value and single SNP–based analysis and to explore their strengths and weaknesses. Simulation studies show that: 1) all three methods can reasonably control the false-positive rate; 2) the minimum p-value method outperforms the entropy-based and the single SNP–based method when only one disease-related SNP occurs within the gene; 3) the entropy-based method outperforms the other methods when there are more than two diseaserelated SNPs in the gene; and 4) the entropy-based method is computationally more efficient than the minimum p-value method. Application to a real data set shows that more significant genes were identified by the entropy-based method than by the other two methods.

Cite this article as:

Kang Guolian, Jiang Bo and Cui Yuehua, Gene-based Genomewide Association Analysis: A Comparison Study, Current Genomics 2013; 14 (4) . https://dx.doi.org/10.2174/13892029113149990001