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Updated: May 2, 2026
08:03
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
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CanSNPer: a hierarchical genotype classifier of clonal pathogens.
Adrian Lärkeryd1, Kerstin Myrtennäs1, Edvin Karlsson1
1Department of Clinical Microbiology, Umeå University, Division of CBRN Security and Defence, FOI, Swedish Defence Research Agency, Department of Clinical Microbiology, The Laboratory for Molecular Infection Medicine Sweden (MIMS) and Department of Chemistry, Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden.
Bioinformatics (Oxford, England)
|February 28, 2014
Summary
CanSNPer is a new pipeline for classifying pathogen genotypes using single nucleotide polymorphisms. This tool helps analyze vast amounts of whole genome sequencing data for molecular epidemiology.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- Advances in pathogen typing methodologies have transformed molecular epidemiology.
- Whole genome sequencing (WGS) generates large datasets, posing challenges for bioinformatics resources and tool development.
- Single nucleotide polymorphisms (SNPs) in pathogen core genomes are key markers for genetic relationship inference due to their stability and amenability to high-throughput detection.
Purpose of the Study:
- To present an efficient and user-friendly genotype classification pipeline.
- To address the challenge of extracting knowledge from extensive sequence data.
Main Methods:
- Developed CanSNPer, a genotype classification pipeline.
- Utilized an expandable database of predefined canonical single nucleotide polymorphisms.
- The pipeline is Python-based.
Main Results:
- CanSNPer provides an efficient method for pathogen genotype classification.
- Facilitates the analysis of large-scale WGS data.
Conclusions:
- CanSNPer offers a solution for analyzing pathogen genetic relationships using SNPs.
- The tool enhances the understanding of infectious diseases through efficient data analysis.
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