![]() They have also been widely adopted for clinical genetic testing. NGS technologies enabled ambitious large-scale genomic sequencing efforts that have transformed our understanding of human health and disease, such The Cancer Genome Atlas, the Centers for Mendelian Genomics, and the UK10K Project. The emergence of next-generation sequencing more than a decade ago represented a major technological advance over traditional sequencing methods. Although NGS technologies are continually evolving, and new capabilities (such as long-read single-molecule sequencing) are emerging, the “best practice” principles in this review should be relevant to clinical variant calling in the long term. ![]() Recommended tools and strategies for calling variants of different classes are also provided, along with guidance on variant review, validation, and benchmarking to ensure optimal performance. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. In this review, I discuss the current best practices for variant calling in clinical sequencing studies, with a particular emphasis on trio sequencing for inherited disorders and somatic mutation detection in cancer patients. Just as NGS technologies have evolved considerably over the past 10 years, so too have the software tools and approaches for detecting sequence variants in clinical samples. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer.
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