Nature Communications · 2019 · 332 citations · 37 references
Life SciencesInfectious DiseasesMicrobiologyGenomicsMetagenomicsMicrobial GenomicsDna SequencingMetagenomic Data Quality ControlPathogen DetectionPathogen GenomicsSequence Quality ControlViral GenomicsClinical Quality MetricsMicrobial Culture IdentificationNext-generation Sequencing ValidationPathogen Genomics DatabasesPublic Domain DatabaseReference Genome AnalysisReference Genome CurationValidation Strategy Development
FDA proactively invests in tools to support innovation of emerging technologies, such as infectious disease next‑generation sequencing (ID‑NGS). The study introduces FDA‑ARGOS, a quality‑controlled reference genome database for diagnostics, and demonstrates its utility through two use cases. The authors provide quality‑control metrics for FDA‑ARGOS and emphasize the need to fill genome quality gaps in the public domain. The database enhances microbial identification accuracy, facilitates Ebola virus target comparison in validation strategies, and could reduce the burden of ID‑NGS clinical trials by serving as an in‑silico comparator.
Abstract FDA proactively invests in tools to support innovation of emerging technologies, such as infectious disease next generation sequencing (ID-NGS). Here, we introduce FDA-ARGOS quality-controlled reference genomes as a public database for diagnostic purposes and demonstrate its utility on the example of two use cases. We provide quality control metrics for the FDA-ARGOS genomic database resource and outline the need for genome quality gap filling in the public domain. In the first use case, we show more accurate microbial identification of Enterococcus avium from metagenomic samples with FDA-ARGOS reference genomes compared to non-curated GenBank genomes. In the second use case, we demonstrate the utility of FDA-ARGOS reference genomes for Ebola virus target sequence comparison as part of a composite validation strategy for ID-NGS diagnostic tests. The use of FDA-ARGOS as an in silico target sequence comparator tool combined with representative clinical testing could reduce the burden for completing ID-NGS clinical trials.
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The Sequence Alignment/Map format and SAMtools
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