PanGIA: A Bioinformatics Pathogen Detection Software for the End-to-End Whole Genome Sequencing Diagnostic System

Next-generation-sequencing (NGS) has great potential for use as an excellent tool for diagnosing infectious disease. General metagenomics taxonomy classifiers have been employed to help identify organisms within clinical... [ view full abstract ]

Next-generation-sequencing (NGS) has great potential for use as an excellent tool for diagnosing infectious disease. General metagenomics taxonomy classifiers have been employed to help identify organisms within clinical samples. However, before NGS can be used as a routine procedure in the clinical microbiology lab, several hurdles must be overcome: (1) provide bioinformatics tools which run effectively on commodity hardware; (2) provide visualizations which allow samples to be analyzed and interpreted by clinicians in a meaningful fashion; (3) provide confidence levels for the reported community profiling; (4) rapidly down select the resulting list of organisms identified with a pre-defined list of pathogens. To address these gaps, we present an intuitive analysis software package, PanGIA, for the execution of routine, automated bioinformatics analysis for NGS. The bioinformatics pipeline leverages BWA-mem to identify ‘where’ reads belong to provide taxonomic identification specific to strain-level. Other than community profiling, PanGIA uses two approaches to obtain a metric of confidence; one relies on uniqueness of sequences and one relies on comparing test samples with control samples. The software includes an associated web-based user interface for job submission and interactive result visualization which provides pathogenic information and real-time filtering results. The pipeline was tested and validated using many synthetic datasets ranging in community composition and complexity and was successfully applied to spiked clinical samples.