Variant pathogenicity scoring and classification and uses thereof
AssigneeIllumina, Inc.
InventorsHong Gao, Kai-How Farh, Jeremy Francis McRae
Life of this patent
Estimating the term…
Abstract
Derivation and use of pathogenicity scores for gene variants are described herein. Applications, uses, and variations of the pathogenicity scoring process include, but are not limited to, the derivation and use of thresholds to characterize a variant as pathogenic or benign, the estimation of selection effects associated with a gene variant, the estimation of genetic disease prevalence using pathogenicity scores, and the recalibration of methods used to assess pathogenicity scores.
Claims21
A method for classifying a variant of interest, the method comprising:
- executing, on one or more processors of a computer system, stored instructions for classifying the variant of interest, wherein the stored instructions, when executed, cause the one or more processors to perform acts comprising:
- generating a pathogenicity score for a variant of interest of a gene using a neural network trained using both human sequence data and non-human primate date sequence data;
- comparing the pathogenicity score for the variant of interest to a gene-specific pathogenicity threshold determined for the gene, wherein different genes have different respective pathogenicity thresholds;
- and
- classifying the variant of interest as a pathogenic variant in response to the pathogenicity score exceeding the gene-specific pathogenicity threshold determined for the gene.
A non-transitory computer-readable medium storing processor- executable instructions that, when executed by one or more processors, cause the one or more processors to perform steps comprising:
- processing a variant of interest for a gene using a pathogenicity scoring neural network to generate a pathogenicity score for the variant of interest, wherein the pathogenicity scoring neural network is trained using both human sequence data and non-human primate date sequence data;
- comparing the pathogenicity score for the variant of interest to a pathogenicity threshold specific to the gene and a benign threshold specific to the gene, wherein different genes have different respective pathogenicity thresholds and benign thresholds;
- and
- classifying the variant of interest as pathogenic, benign, or neither pathogenic or benign based on the comparison of the pathogenicity score to the pathogenicity threshold specific to the gene and the comparison of the pathogenicity score to the benign threshold specific to the gene.
A variant classification system, comprising:
- one or more memory structures encoding processor-executable instructions;
- one or more processors in communication with the one or more memory structures, wherein the one or more processors execute the instructions to perform operations comprising:
- generating a pathogenicity score for a variant of interest of a gene using a neural network trained using both human sequence data and non-human primate date sequence data;
- comparing the pathogenicity score for the variant of interest to a pathogenicity threshold specific to the gene and a benign threshold specific to the gene, wherein different genes have different respective pathogenicity thresholds and benign thresholds;
- and
- classifying the variant of interest as pathogenic, benign, or neither pathogenic or benign based on the comparison of the pathogenicity score to the pathogenicity threshold specific to the gene and the comparison of the pathogenicity score to the benign threshold specific to the gene.
Dependencies are inferred from the claim text.