A new set of in silico tools to support the interpretation of ATM missense variants using graphical analysis

Establishing the pathogenic nature of variants in ATM, a gene associated with breast cancer and other hereditary cancers, is crucial for providing patients with adequate care. Unfortunately, achieving good variant classifications is still an unsolved problem. Here, this challenge is addressed, extending the range of in silico tools with a series of graphical tools devised for the analysis of computational evidence by healthcare professionals.We propose a family of fast and easy-to-use graphical representations in which the impact of a variant is considered relative to other pathogenic and benign variants.

Source: Journal of Molecular Diagnostics - October 18, 2023 Category: Pathology Authors: Luz Marina Porras, Natalia Padilla, Alejandro Moles-Fern ández, Lidia Feliubadaló, Marta Santamariña-Pena, Alysson T. Sánchez, Anael López-Novo, Ana Blanco, Miguel de la Hoya, Ignacio J. Molina, Ana Osorio, Marta Pineda, Daniel Rueda, Clara Ruiz-Pont Tags: Regular Article Source Type: research