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Disease variant prediction with deep generative models of evolutionary data | Nature

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A new computational method, EVE, classifies human genetic variants in disease genes using deep generative models trained solely on evolutionary sequences.

Subjects Computational models Disease genetics Genetic variation Genetics research Machine learning A Publisher Correction to this article was published on 17 December 2021 This article has been updated Abstract Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences 1 , 2 , 3 . In principle, computational methods could support the large-scale interpretation of genetic variants. However, state-of-the-art methods 4 , 5 , 6 , 7 , 8

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