MiGA takes variety of inputs to help its users make taxonomic inferences about their draft or whole genome sequences. It uses a combination of the genome-aggregate Average Nucleotide Identity concept, or ANI, and the Average Amino-acid Identity, AAI, to taxonomically classify a genomic sequence against the genome sequences in its reference database. Part of MiGA’s strength lies in the >10,000 reference genomes that make up its database and an efficient heuristic algorithm to search a query genome against all of these genomes. The reference database is maintained in a way which allows it to be regularly updated and improved with minimal downtime. This ensures consistently improved accuracy of classification without a large impact to its users.