Fig. 5

Developed scripts and published programs (i.e. black letters) with their corresponding effects (i.e. green letters) implemented in the driving script ‘microbial-GWAS’ performing microbial GWAS integrating Linear Mixed Model (LMM) for population structure correction. Based on the LMM integrated in GEMMA, the sequential workflow called ‘microbial-GWAS’ is written in R and Python 2.7. It runs successively scripts called ‘binary’, ‘panGWAS’, ‘coreGenVarNb’, ‘overImpacted’ and ‘AllResults’ in order to standardize SNPs, InDels and genes as binary data, compute Kinship matrix, fit a LMM and perform Wald tests, as well as detect coregenome variants presenting high gene densities (i.e. hotspots of variants) and high functional impacts (i.e. non-synonymous variants)