Enhanced Pathogen Detection Through Metagenome Assembly Reference Optimization
Project Premonition aims to detect pathogens before they cause outbreaks by turning mosquitoes into devices that collect data from animals in the environment. First, mosquitoes are collected using robots. Then, each metagenome sample goes through DNA sequencing. Finally, we use metagenome alignment to identify what pathogens exist in each sample. For my capstone project, I optimized this metagenome alignment step by using data science to reduce redundancy and contamination in our reference genome database. This data is both large and complex, containing over 600,000 genomes and 1.4 Tbp (tera base pairs).