Recurrent neural network-based variant pathogenicity classifier

A variant pathogenicity classifier, comprising:

• a recurrent neural network which runs on numerous processors coupled to memory and is trained to determine pathogenicity of variants;
• wherein the recurrent neural network is trained using, as input, benign training example pairs and pathogenic training example pairs of reference protein sequences and alternative protein sequences;
• wherein the alternative protein sequences are generated from benign variants and pathogenic variants;
• and
• wherein the benign variants include common human missense variants and non-human primate missense variants occurring on alternative non-human primate codon sequences that share matching reference codon sequences with humans.

A system, comprising:

• a variant pathogenicity classifier which runs on numerous processors coupled to memory and is trained to determine pathogenicity of variants;
• wherein the variant pathogenicity classifier is trained using, as input, benign training example pairs and pathogenic training example pairs of reference protein sequences and alternative protein sequences;
• wherein the alternative protein sequences are generated from benign variants and pathogenic variants;
• and
• wherein the benign variants include common human missense variants and non-human primate missense variants occurring on alternative non-human primate codon sequences that share matching reference codon sequences with humans.