OHEJP-RaDAR-D-JRP3-1.6-1.7 GWAS-based method for genomic data analysis / Development of regression model for genomic data analysis

Background
Genome Wide Association Studies (GWAS) are hypothesis-free methods for identifying genetic variations associated with particular phenotypic traits within a population (Juran and Lazaridis, 2011;Visscher et al., 2017). Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes (Power et al., 2017).
Given the availability of large panels of bacterial genomes combined with phenotypic data in public databases, GWAS have shown promising results for genetic marker discovery and as emerged as a fundamental task in bacterial genomics (Falush, 2016). GWAS will provide microbiologist with an enhanced insight into genotype to phenotype correlations, including complex traits such as virulence, persistence, biofilm formation, epidemicity, host preference and antibiotic resistance (Laabei et al., 2014;Brynildsrud et al., 2016;Lees et al., 2017;Jaillard et al., 2018;Fritsch et al., 2019).