ABSTRACT
Recent advances in next-generation sequencing (NGS) methods have greatly promoted the NGS-based genome/exome studies in discovering genetic variants for human diseases. Whole-genome sequencing (WGS) remains prohibitively expensive and requires concurrent development of bioinformatics approaches. Whole exome sequencing (WES), focusing on only the protein-coding sequence of the human genome, is now a widely used cost-effective approach that could identify disease-causing variants. Here, we provide the performance assessment of various aligners and variant calling tools using simulated and standard human exome datasets and highlight their combinations that improve the detection of single nucleotide variants (SNVs) and InDels. Further, we provide general recommendations for bioinformatic analysis for WES methods, focusing on variant filtering and prioritization for clinical use.
