1. Development of an Evidence-Based Algorithm in WES-Based Diagnostics

Development of an Evidence-Based Algorithm in WES-Based Diagnostics

Dr. Peter Bauer, MD Maximilian E. R. Weiss Omid Paknia, PhD Martin Werber Aida M. Bertoli-Avella, MD Zafer Yüksel, MD Krishna Kumar Kandaswamy, PhD Malgorzata Bochinska Gabriela-Elena Oprea, PhD Shivendra Kishore, PhD Volkmar Weckesser, Dr Ellen Karges, Ms Prof. Arndt Rolfs, MD
April 11, 2018

These findings were presented at the American College of Medical Genetics and Genomics (ACMG ) annual meeting 2017.

Sensitivity of whole exome sequencing (WES) is not well-defined. We applied very low thresholds in WES-associated variant calling to also enable investigation of candidate variants that are commonly neglected. As Sanger sequencing revealed ~5% of these to be true positives (Figure 1), we considered numerous variant-specific features (Tables 1 and 2) for the development of a robust predictor for true and false positives. Iterative rounds of receiver operating characteristic (ROC) curve generation identified features and corresponding thresholds with high predictive value (Figure 2). In a corresponding workflow for our data, 91.3% of variants can be pre-classified with 100% specificity and 99.8% sensitivity, while the remaining 8.7% of variants require confirmatory Sanger sequencing (Figure 3).