Artificial intelligence (AI)-assisted exome reanalysis greatly aids in the identification of new positive cases and reduces analysis time in a clinical diagnostic laboratory.

Journal: Genetics in medicine : official journal of the American College of Medical Genetics
Published Date:

Abstract

PURPOSE: Artificial intelligence (AI) and variant prioritization tools for genomic variant analysis are being rapidly developed for use in clinical diagnostic testing. However, their clinical utility and reliability are currently limited. Therefore, we performed a validation of a commercial AI tool (Moon) and a comprehensive reanalysis of previously collected clinical exome sequencing cases using an open-source variant prioritization tool (Exomiser) and the now-validated AI tool to test their feasibility in clinical diagnostics.

Authors

  • Timothy D O'Brien
    Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR. Electronic address: obrietim@ohsu.edu.
  • N Eleanor Campbell
    Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR.
  • Amiee B Potter
    Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR.
  • John H Letaw
    Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR.
  • Arpita Kulkarni
    Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR.
  • C Sue Richards
    Knight Diagnostic Laboratories, Oregon Health & Science University, Portland, OR; Department of Molecular and Medical Genetics, School of Medicine, Oregon Health & Science University, Portland, OR.