Towards best practice in cancer mutation detection with whole-genome and whole-exome sequencing

Abstract Clinical applications of precision oncology require accurate tests that can distinguish cancer-specific mutations from errors introduced at each step of next generation sequencing (NGS). For NGS to successfully improve patient lives, discriminating between true mutations and artifacts is crucial. To date, no study has addressed the effects of cross site reproducibility together with the potentially influential interactions between biological, technical, and computational factors on the accurate identification of variants. Here we systematically interrogated somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy. Different types of samples with varying input amount and tumor purity were processed using multiple library construction protocols. Whole-genome (WGS) and whole-exome sequencing (WES) were carried out at six sequencing centers followed by processing with nine bioinformatics pipelines to evaluate reproducibility. We identified artifacts of C>A mutations in WES due to sample and library processing and highlighted limitations of bioinformatics tools for artifact detection and removal. By examining the interactions and effects of NGS platforms, library preparation protocol, tumor content, read coverage, and bioinformatics processes concomitantly, here we recommend actionable practices for cancer mutation detection experiments and analysis using NGS technologies.