RESUMO
With the advent of high-throughput DNA sequencing technologies, traditional methodologies for taxonomic classification of bacteria as DNA-DNA hybridization and 16S rRNA identity analyses are being challenged by the development of a fast-growing number of genomic metrics. The large amount of portable and digitized genome sequences available in public repositories constitutes an invaluable data for bacterial classification. Consequently, several genomic metrics and tools were developed to aid the interpretation of these massive data. Genomic metrics are based on the assumption that higher genome similarities would reflect closer phylogenetic relationships. Different metrics would vary in their methodology of analysis, resolution power, limitations and easiness of use. The aim of this review is to highlight the differences among available genome-based methods and tools to provide a guide for in silico bacterial identification and classification.
