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

Zachary S. Bohannan, Antonina Mitrofanova

Research output: Contribution to journalReview article

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)561-569
Number of pages9
JournalComputational and Structural Biotechnology Journal
Volume17
DOIs
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

Keywords

  • Bioinformatics
  • Clinical oncology
  • Computational biology
  • Genomics
  • Variant calling

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