title: SuperPhy: predictive genomics for the bacterial pathogen Escherichia coli.
abstract: BACKGROUND
  Predictive genomics is the translation of raw genome sequence data into a phenotypic assessment of the organism. For bacterial pathogens, these phenotypes can range from environmental survivability, to the severity of human disease. Significant progress has been made in the development of generic tools for genomic analyses that are broadly applicable to all microorganisms; however, a fundamental missing component is the ability to analyze genomic data in the context of organism-specific phenotypic knowledge, which has been accumulated from decades of research and can provide a meaningful interpretation of genome sequence data.
  
  
  RESULTS
  In this study, we present SuperPhy, an online predictive genomics platform ( http://lfz.corefacility.ca/superphy/ ) for Escherichia coli. The platform integrates the analytical tools and genome sequence data for all publicly available E. coli genomes and facilitates the upload of new genome sequences from users under public or private settings. SuperPhy provides real-time analyses of thousands of genome sequences with results that are understandable and useful to a wide community, including those in the fields of clinical medicine, epidemiology, ecology, and evolution. SuperPhy includes identification of: 1) virulence and antimicrobial resistance determinants 2) statistical associations between genotypes, biomarkers, geospatial distribution, host, source, and phylogenetic clade; 3) the identification of biomarkers for groups of genomes on the based presence/absence of specific genomic regions and single-nucleotide polymorphisms and 4) in silico Shiga-toxin subtype.
  
  
  CONCLUSIONS
  SuperPhy is a predictive genomics platform that attempts to provide an essential link between the vast amounts of genome information currently being generated and phenotypic knowledge in an organism-specific context.
authors.affiliation: National Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
authors.forename: Matthew D
authors.initials: MD
authors.lastname: Whiteside
authors.affiliation: National Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada. chad.laing@canada.ca.
authors.forename: Chad R
authors.initials: CR
authors.lastname: Laing
authors.affiliation: National Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
authors.forename: Akiff
authors.initials: A
authors.lastname: Manji
authors.affiliation: National Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
authors.forename: Peter
authors.initials: P
authors.lastname: Kruczkiewicz
authors.affiliation: National Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
authors.forename: Eduardo N
authors.initials: EN
authors.lastname: Taboada
authors.affiliation: National Microbiology Laboratory @ Lethbridge, Public Health Agency of Canada, Lethbridge, AB, T1J 3Z4, Canada.
authors.forename: Victor P J
authors.initials: VP
authors.lastname: Gannon
mesh_terms: D030561:Databases, Nucleic Acid; D024881:Drug Resistance, Bacterial; D004926:Escherichia coli / Q000235:genetics*; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods*; D010641:Phenotype; D017422:Sequence Analysis, DNA; D012984:Software; D037521:Virulence Factors / Q000235:genetics
chemical_list: D037521:Virulence Factors
keywords: Anti-microbial resistance; Bioinformatics; Comparative genomics; Epidemiology; Population genomics; Software; Virulence factors