Across all genomic profiling applications, from research to molecular testing and pharmaceutical development, the ability to identify and interpret potentially actionable genetic alterations is becoming increasingly difficult. As NGS tests increase in size, more biomarkers are uncovered, and demand for routine testing soars, labs need the most up-to-date, biological and clinical information directly in their informatics pipeline to identify and classify variants rapidly and confidently.