Calling Variants in the Clinic: Informed Variant Calling Decisions Based on Biological, Clinical, and Laboratory Variables

• Main Authors: Zachary S. Bohannan, Antonina Mitrofanova
• Format: Article
• Language: English
• Published: Elsevier 2019-01-01
• Series: Computational and Structural Biotechnology Journal
• Online Access: http://www.sciencedirect.com/science/article/pii/S2001037018302848

Deep sequencing genomic analysis is becoming increasingly common in clinical research and practice, enabling accurate identification of diagnostic, prognostic, and predictive determinants. Variant calling, distinguishing between true mutations and experimental errors, is a central task of genomic analysis and often requires sophisticated statistical, computational, and/or heuristic techniques. Although variant callers seek to overcome noise inherent in biological experiments, variant calling can be significantly affected by outside factors including those used to prepare, store, and analyze samples. The goal of this review is to discuss known experimental features, such as sample preparation, library preparation, and sequencing, alongside diverse biological and clinical variables, and evaluate their effect on variant caller selection and optimization. Keywords: Variant calling, Genomics, Clinical oncology, Bioinformatics, Computational biology