This project aims to investigate the genetic links between a large-scale (~2200) E. coli strain library and exhibited phenotype of said strains in a wide range of antibiotics and other antimicrobial compounds. To accomplish this we set up a bioinformatic pipeline starting from assembled sequences, annotating them, performing pangenomic analyses and lastly correlating genes to expressed phenotype using a linear mixed model approach in a tool called DBGWAS. This platform will initially be tested on an existing dataset of multiple antibiotics and heavy metals, in order to confirm hits we have identified manually through another approach. The next step after this is to apply the platform to analyze new datasets of the same library exposed to approved and in development antibiotics, testing for genes related to resilience/susceptibility in sub-inhibitory concentrations.