Comparing Classifications from Multiple Variant Annotation Software Solutions Using Real-World Next Generation Sequencing Data from Oncology Testing

Abstract

Variant annotation is an important step in deciphering the functional impact of genomic variants and their association with diseases. In this study, we analyzed 80 pan-cancer cases that underwent comprehensive genomic testing and compared the auto-classified variant tiers among four globally-available software solutions for variant interpretation from Roche, SOPHiA GENETICS, QIAGEN, and Genoox. The results revealed striking differences in tier classifications, which are believed to be a result of several factors, including subjectivity in the AMP/ASCO/CAP guidelines, threshold settings for variant allele frequencies and population allele frequencies, as well as variation in disease ontologies. Although the software tools described here provide a time-saving and repeatable process for interpretation of genomic data, it is crucial to understand the nuances and various settings for these solutions, as they can strongly influence variant tier classifications and downstream management.