Best practices for variant calling in clinical sequencing
Abstract 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...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2020-10-01
|
| Series: | Genome Medicine |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s13073-020-00791-w |
| _version_ | 1818978922906255360 |
|---|---|
| author | Daniel C. Koboldt |
| author_facet | Daniel C. Koboldt |
| author_sort | Daniel C. Koboldt |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-20T16:51:20Z |
| format | Article |
| id | doaj.art-cb62fd041afe4326a8b1ee031cfe29f4 |
| institution | Directory Open Access Journal |
| issn | 1756-994X |
| language | English |
| last_indexed | 2024-12-20T16:51:20Z |
| publishDate | 2020-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Medicine |
| spelling | doaj.art-cb62fd041afe4326a8b1ee031cfe29f42022-12-21T19:32:49ZengBMCGenome Medicine1756-994X2020-10-0112111310.1186/s13073-020-00791-wBest practices for variant calling in clinical sequencingDaniel C. Koboldt0Steve and Cindy Rasmussen Institute for Genomic Medicine at Nationwide Children’s HospitalAbstract 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.http://link.springer.com/article/10.1186/s13073-020-00791-wNext-generation sequencingVariant callingMutation detectionClinical sequencingCancer sequencingBest practices |
| spellingShingle | Daniel C. Koboldt Best practices for variant calling in clinical sequencing Genome Medicine Next-generation sequencing Variant calling Mutation detection Clinical sequencing Cancer sequencing Best practices |
| title | Best practices for variant calling in clinical sequencing |
| title_full | Best practices for variant calling in clinical sequencing |
| title_fullStr | Best practices for variant calling in clinical sequencing |
| title_full_unstemmed | Best practices for variant calling in clinical sequencing |
| title_short | Best practices for variant calling in clinical sequencing |
| title_sort | best practices for variant calling in clinical sequencing |
| topic | Next-generation sequencing Variant calling Mutation detection Clinical sequencing Cancer sequencing Best practices |
| url | http://link.springer.com/article/10.1186/s13073-020-00791-w |
| work_keys_str_mv | AT danielckoboldt bestpracticesforvariantcallinginclinicalsequencing |