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《Journal of Qufu Normal University(Natural Science)》 2018-04
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A Comparison of Statistical Methods for Meta-Analysis in Genome-Wide Association Studies

BI Hui-li;School of Statistics,Qufu Normal University;  
Genome-wide association studies(GWAS)have identified many genetic variants that are associated with complex human traits and diseases.Due to ethical and privacy issues,the individual-level genotype and phenotype data are often not easily accessible.In contrast,the GWAS summary statistics are becoming widely available.As meta-analysis combining multiple GWAS,it can increase the sample size substantially and thus increase the statistical power to detect genetic variants.Therefore,many statistical methods for GWAS meta-analysis have been proposed.As the number of meta-analyses of GWAS increasing,researchers need some useful guidelines to select appropriate statistical methods for the application of real data.In this paper,we evaluate the performance of some existing meta-analysis methods in GWAS,compare the powers of these methods using extensive simulation studies and report the advantages and disadvantages of each method.
【CateGory Index】: Q811.4
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