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Backward compatibility of whole genome sequencing data with MLVA typing using a new MLVAtype shiny application for Vibrio cholerae.

Jérôme AmbroiseLéonid M IrengeJean-François DurantBertrand BearzattoGodfrey BwireO Colin StineJean-Luc Gala
Published in: PloS one (2019)
As NGS read lengths and qualities tend to increase with time, one may expect the increase of k-mer size in a near future. Using MLVAType application with a longer k-mer size will then efficiently retrieve MLVA profiles from WGS data while avoiding censored estimation.
Keyphrases
  • electronic health record
  • big data
  • single molecule
  • machine learning
  • genetic diversity