Genes, Vol. 14, Pages 1600: MAGI-ACMG: Algorithm for the Classification of Variants according to ACMG and ACGS Recommendations
Genes doi: 10.3390/genes14081600
Authors:
Francesca Cristofoli
Muharrem Daja
Paolo Enrico Maltese
Giulia Guerri
Benedetta Tanzi
Roberta Miotto
Gabriele Bonetti
Jan Miertus
Pietro Chiurazzi
Liborio Stuppia
Valentina Gatta
Stefano Cecchin
Matteo Bertelli
Giuseppe Marceddu
We have developed MAGI-ACMG, a classification algorithm that allows the classification of sequencing variants (single nucleotide or small indels) according to the recommendations of the American College of Medical Genetics (ACMG) and the Association for Clinical Genomic Science (ACGS). The MAGI-ACMG classification algorithm uses information retrieved through the VarSome Application Programming Interface (API), integrates the AutoPVS1 tool in order to evaluate more precisely the attribution of the PVS1 criterion, and performs the customized assignment of specific criteria. In addition, we propose a sub-classification scheme for variants of uncertain significance (VUS) according to their proximity either towards the “likely pathogenic” or “likely benign” classes. We also conceived a pathogenicity potential criterion (P_POT) as a proxy for segregation criteria that might be added to a VUS after posterior testing, thus allowing it to upgrade its clinical significance in a diagnostic reporting setting. Finally, we have developed a user-friendly web application based on the MAGI-ACMG algorithm, available to geneticists for variant interpretation.
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