Infectious diseases impact public health globally. Pathogen outbreaks affect the life of patients and create a high economical burden. Early detection and control of outbreaks is therefore key to protecting public health.
Whole genome analysis offers unique advantages when used for typing and characterizing microbial isolates. Whole genome data reveals the full picture providing taxonomic information and insight into factors like antimicrobial resistance. Once a pathogenic microbe is typed and characterized, comparative whole genome SNP analysis is the most accurate path to tracking a pathogen contamination back to the source.
While crucial for outbreak control, whole genome analysis also enables quality control of starter cultures and biotechnologically valuable strains.
Streamlined and pre-configured analysis workflows guide users through NGS data analysis following best practices.
Take advantage of metadata management. Metadata tables track sample information like geographical source or patient data and and link the so called metadata to analysis results such as sequence types or identified resistance genes. This way you can select with confidence relevant subsets of samples and subject them to downstream analyses directly from within the metadata table.
Adjust the resolution to your need when typing new isolates. Rely on NGS-MLST for epidemiological clustering by sequence type, then leverage the power of whole genome SNP phylogenies to resolve relatedness of microbes with maximum resolution.
Samples, sample information (metadata) and results can be accessed from a convenient analysis dashboard.
Preconfigured and customizable workflows streamline typing. In one analysis workflow, taking raw whole genome isolate data as input, you confirm the identity and characteristics of microbes, revealing:
Preconfigured and customizable workflows streamline phylogenetic analysis:
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