The DOI matches its Crossref record; 127 of the 127 references it cites were found in a registry or an index.
Best practices for variant calling in clinical sequencing
Open accessAbstract
Next-generation sequencing technologies have enabled a dramatic expansion of clinical genetic testing both for inherited conditions and diseases such as cancer. Accurate variant calling in NGS data is a critical step upon which virtually all downstream analysis and interpretation processes rely. 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. 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. I describe the relative strengths and weaknesses of panel, exome, and whole-genome sequencing for variant detection. 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. 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.
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A framework for variation discovery and genotyping using next-generation DNA sequencing data
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Cited by
Next-generation data filtering in the genomics era
Hemstrom, W., Grummer, J. A., Luikart, G., & Christie, M. R. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00738-6 · Cited by 77
Metadata
- Authors
- Koboldt, D. C.
- Venue
- Genome Medicine
- Published
- 2020-10-26
- Volume
- 12
- Issue
- 1
- Pages
- 91-91
- ISSN
- 1756-994X (ISSN-L)
- OpenAlex
- W3093528466
- Cited by
- 384
- References
- 127
- FWCI
- 21.32
- Type
- journal article
- Language
- en
- Open access
- gold
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