Genome-by-genome approach for fast bacterial genealogical relationship evaluation

Abstract

Motivation: Large-scale whole-genome sequencing dataset-based studies are becoming increasingly common in pathogen surveillance and outbreak investigations. A highly discriminative and time-efficient bioinformatics tool is needed to transform large amounts of sequencing data into usable biological information. To replace the intuitive, yet inefficient, way of gene-by-gene allele calling algorithm, a new algorithm using genome-by-genome approach was developed. Results: Tests showed that the program equipped with the new algorithm achieved significant improvements in allele calling efficiency compared to a conventional gene-by-gene approach. The new program, Fast-GeP, rendered a fast and easy way to infer high-resolution genealogical relationships between bacterial isolates using whole-genome sequencing data.