Challenges of Accuracy in Germline Clinical Sequencing Data
Justin Zook, Ryan Poplin, Mark DePristo
Physicians are increasingly using clinical sequencing tests to establish diagnoses of patients who might have genetic disorders, which means that accuracy of sequencing and interpretation are important elements in ensuring the benefits of genetic testing. In the past, clinical sequencing tests were designed to detect specific prespecified or unknown variants that were in limited regions of an individual's genome. The raw data for each detected variant was then manually reviewed for errors in sequencing and for its potential clinical importance. Newer technology allows for assessment of exomes or entire genomes and can identify millions of genetic variants in each sequenced individual. The shift from limited targeted sequencing to genome sequencing requires automated algorithms to parse through raw data to help distinguish true variants from those caused by systematic errors. Errors can result from incorrectly read bases in particular DNA molecule regions that are difficult to sequence and from mapping short sequences incorrectly to the human reference genome. New developments in sequencing and analysis, as well as standard quality measures, are critical to ensure the accuracy of sequencing results intended for medical use.
, Poplin, R.
and DePristo, M.
Challenges of Accuracy in Germline Clinical Sequencing Data, Jama-Journal of the American Medical Association, [online], https://doi.org/10.1001/jama.2021.0407, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=926623
(Accessed August 17, 2022)