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Lärkeryd, Adrian; Myrtennäs, Kerstin; Karlsson, Edvin; Dwibedi, Chinmay Kumar; Forsman, Mats; Larsson, Pär; Johansson, Anders; Sjödin, Andreas
Bioinformatics (Oxford, England), 06/2014, Volume: 30, Issue: 12Journal Article
Advances in typing methodologies have recently reformed the field of molecular epidemiology of pathogens. The falling cost of sequencing technologies is creating a deluge of whole genome sequencing data that burdens bioinformatics resources and tool development. In particular, single nucleotide polymorphisms in core genomes of pathogens are recognized as the most important markers for inferring genetic relationships because they are evolutionarily stable and amenable to high-throughput detection methods. Sequence data will provide an excellent opportunity to extend our understanding of infectious disease when the challenge of extracting knowledge from available sequence resources is met. Here, we present an efficient and user-friendly genotype classification pipeline, CanSNPer, based on an easily expandable database of predefined canonical single nucleotide polymorphisms. All documentation and Python-based source code for the CanSNPer are freely available at http://github.com/adrlar/CanSNPer.
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