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The efficiency of single SNP and SNP-set analysis in genome-wide association studies

Sookkhee, S., Kirdwichai, P. and Baksh, F. (2019) The efficiency of single SNP and SNP-set analysis in genome-wide association studies. Songklanakarin Journal of Science and Technology. ISSN 0125-3395 (In Press)

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Abstract/Summary

The objective of this research is to compare and identify effective methods for the identification of gene loci associated with a disease outcome in the analysis of genome-wide data. We evaluate three methods which are single SNP analysis, Sequence Kernel Association Test (SKAT) and the recently proposed Generalized Higher Criticism (GHC). The simulated data used in this research were constructed from a control data set in a study of Crohn's disease. True positive (TP) and false positive rate (FP) were evaluated under different genetic models for disease with significant thresholds adjusted for multiple hypothesis testing based on the permutation method. The findings are mixed with all three methods giving similar TP rates under some disease models and different rates for other models. Overall, GHC is shown to be preferable in terms of error rates but it is disadvantageous in terms of computational efficiency.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics > Applied Statistics
ID Code:93703
Publisher:Prince of Songkla University

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