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Genome-by-genome approach for fast bacterial genealogical relationship evaluation
- Source :
- Bioinformatics. 34:3025-3027
- Publication Year :
- 2018
- Publisher :
- Oxford University Press (OUP), 2018.
-
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.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Whole genome sequencing
Genome
Bacteria
Whole Genome Sequencing
Computer science
030106 microbiology
Computational biology
Biochemistry
Pedigree
Computer Science Applications
03 medical and health sciences
Computational Mathematics
ComputingMethodologies_PATTERNRECOGNITION
030104 developmental biology
Computational Theory and Mathematics
Allele
Molecular Biology
Algorithms
Software
Subjects
Details
- ISSN :
- 14602059 and 13674803
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....ae27383a58879e85abcd11427a75ab4b
- Full Text :
- https://doi.org/10.1093/bioinformatics/bty195