Bioinformatics, Sequencing Accuracy, and the Credibility of Clinical Genomics
Menée à partir de données portant sur 1 072 patients atteints d'un cancer de la prostate (âge moyen au diagnostic : 63,7 ans) et sur 1 295 patients atteints d'un mélanome (âge moyen au diagnostic : 59,8 ans), cette étude compare la performance de deux méthodes de détection de variants constitutionnels pathogènes, l'une utilisant la version 3.7 du "Genome Analysis Toolkit" (méthode standard), l'autre utilisant la version 0.6.0 du logiciel DeepVariant, un outil employant les technologies de l'intelligence artificielle
The adoption of clinical exome and whole-genome sequencing based on next-generation sequencing technologies has increased rapidly over the last decade; this has been accelerated by increasing coverage of these services by private and public insurers. Examples of use include tumor and germline sequencing in patients with cancer, rapid turn-around sequencing of the genomes of critically ill neonates to diagnose mendelian conditions, and noninvasive prenatal testing for reproductive decision-making. The accuracy of sequencing results is of paramount importance to patients, clinicians, and those paying for testing services; inaccuracy can affect not only the tested individual, but their extended biological family. Understanding what accuracy means in the context of genome sequencing is a challenge. In the genomics community accuracy is often described using 2 terms: analytic validity, eg, does the sequencing process reliably detect variations that are present in an individual’s genome; and clinical validity, eg, are the variants detected reliably related to health outcomes.
JAMA , éditorial, 2019