Robustification of GWAS to explore effective SNPs addressing the challenges of hidden population stratification and polygenic effects.

ABSTRACT: Genome-wide association studies (GWAS) play a vital role in identifying important genes those is associated with the phenotypic variations of living organisms. There are several statistical methods for GWAS including the linear mixed model (LMM) which is popular for addressing the challenges of hidden population stratification and polygenic effects. However, most of these methods including LMM are sensitive to phenotypic outliers that may lead the misleading results. To overcome this problem, in this paper, we proposed a way to robustify the LMM approach for reducing the influence of outlying observations using the β-divergence method. The performance of the proposed method was investigated using both synthetic and real data analysis. Simulation results showed that the proposed method perf

SUBMITTER: Akond Z 

PROVIDER: S-EPMC8219685 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature