Strategy for sensitive and specific somatic SNV/InDel calling: Leveraging different callers with in-house generated gold standard variant sets.

Abstract

e13104 Background: Somatic mutation calling is critical for cancer genotyping. Although rapid development of mutation detection is witnessed with the maturity of NGS, the need for high sensitivity often results in compromised specificity and manual inspection. Here, we propose a methodology that leverages different variant callers to account for specificity without compromising sensitivity. Methods: We designed a cohort of training samples (n = 22), each with known set of SNVs/InDels that were discovered by KEW CANCERPLEX platform. We assessed the performance of four prevailing mutation callers that utilize different statistical approaches and therefore have different calls, using the training samples. We optimized the parameters of the four variant callers to detect all expected variants. We then examined the intersections of every combination of the four callers and identified the best one that eliminated the highest rate of false calls. A customized tool was developed for the intersection of component SNVs and InDels and the report differences among different callers. We also collected another set of validation samples (n = 28), each with true mutations that were both curated and orthogonally validated. We used this set to further test the efficacy of the refined calling strategy. Results: From the training samples, we chose the combination that provides highest sensitivity and specificity. This refined mutation calling strategy removed ~20% false SNV calls and ~50% false InDel calls in average for each sample. This result was further confirmed by the validation samples. Conclusions: The curated set of mutations from the genetic test platforms can provide valuable gold standard to test and tune mutation callers. The conclusions drawn from the curated variants are in line with the experimentally validated variants and showcase the validity of this practice, which we applied to demonstrate that the strategy of intersecting variants from optimized variant callers will generate mutation calls of higher specificity without compromising sensitivity. This methodology reduces the number of variants for curation and improves curation procedures and turn-around time.