A practical guide to filtering and prioritizing genetic variants

Abstract

Next-generation sequencing (NGS) of whole genomes and exomes is a powerful tool in biomedical research and clinical diagnostics. However, the vast amount of data produced by NGS introduces new challenges and opportunities, many of which require novel computational and theoretical approaches when it comes to identifying the causal variant(s) for a disease of interest. While workflows and associated software to process raw data and produce high-confidence variant calls have significantly improved, filtering tens of thousands of candidates to identify a subset relevant to a specific study is still a complex exercise best left to bioinformaticists. However, as this prioritization procedure requires biological/biomedical reasoning, biologists and clinicians are increasingly motivated to handle the task themselves. Here, we describe a set of guidelines, tools, and online resources that can be used to identify functional variants from whole-genome and whole-exome variant calls and then prioritize these variants with potential associations to phenotypes of interest. Insights gained from a recently published analysis of protein-coding gene variation in >60,000 humans by the Exome Aggregation Consortium (ExAC) are also taken into account.