Identification of candidate genomic regions by integrating cluster analysis and genome-wide association studies

Authors

Princess Silva Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
Joverlyn Gaudillo Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños and Domingo AI Research Center
Ranzivelle Marianne Roxas-Villanueva Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños
Beatrice Tiangco National Institutes of Health, University of the Philippines Manila and Department of Medicine, The Medical City
Julianne Vilela Philippine Genome Center Program for Agriculture, Office of the Vice Chancellor for Research and Extension, University of the Philippines Los Baños
Mario Domingo Domingo AI Research Center
Jason Albia Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños and Domingo AI Research Center

Abstract

By identifying genomic variants responsible for life-threatening complex disorders, genome-wide association studies (GWAS) has gained great potential in improving precision medicine. However, due to the large number of association tests it employs, it becomes susceptible to error rate inflation and decrease in statistical power. This study aims to address these problems by integrating cluster analysis and GWAS in order to identify candidate genomic regions of possible relevance to a phenotype. This integrative approach reduces the number of tests by focusing more on significant genetic loci and the variants residing therein. Using Hamming distance as the similarity measure we conducted cluster analysis on SNPs associated with HBsAg seroclearance and subjected all the resulting SNP-sets to a Hamming-distance based association test. Results showed that all SNP-sets are significantly associated with HBsAg seroclearance. Furthermore, the set which obtained the highest degree of association contain SNPs which belong to the locus 11p which has been previously linked with HBsAg positivity.

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Issue

2021: Proceedings of the 39th Samahang Pisika ng Pilipinas Physics Conference

Article ID

SPP-2021-2G-02

Section

Biological and Medical Physics

Published

2021-10-03

How to Cite

[1]

P Silva, J Gaudillo, RM Roxas-Villanueva, B Tiangco, J Vilela, M Domingo, and J Albia, Identification of candidate genomic regions by integrating cluster analysis and genome-wide association studies, Proceedings of the Samahang Pisika ng Pilipinas 39, SPP-2021-2G-02 (2021). URL: https://proceedings.spp-online.org/article/view/SPP-2021-2G-02.