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

Zhang, Ji; Xiong, Yanwen; Rogers, Lynn; Carter, Glen P; French, Nigel · Bioinformatics · 2018

basic_science · Level V

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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. AVAILABILITY AND IMPLEMENTATION: FAST-GeP is freely available from: https://github.com/jizhang-nz/fast-GeP. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Medical subject headings