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

Bioinformatics. 2018 Sep 1;34(17):3025-3027. doi: 10.1093/bioinformatics/bty195.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Bacteria / genetics*
  • Genome*
  • Pedigree
  • Software
  • Whole Genome Sequencing