PanelApp crowdsources expert knowledge to establish consensus diagnostic gene panels

Abstract

I ndividual genomes contain millions of genetic variants. When considering which variants may be causative for a given rare genetic disease, applying filtering criteria (such as allele frequency, predicted variant consequence, familial segregation and mode of inheritance) decreases this number to hundreds of variants. However, such a number remains labor intensive for a diagnostic genetic testing laboratory to interpret as part of routine service for each patient or family. A list of genes with evidence of disease causation in the condition being assessed aids in prioritizing and ranking the variants. This prioritization decreases the number of candidates that laboratories or clinical geneticists must assess to identify the likely causative variants for clinical reporting. Established lists of genes with clear evidence of disease causation (referred to herein as virtual gene panels) are therefore a highly effective tool in variant prioritization.