Community assignments in identity by descent networks and genetic variant origination
AssigneeAncestry.com DNA, LLC
InventorsJake Kelly Byrnes, Julie M. Granka, Shannon Hateley, Ladan Doroud
Life of this patent
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AssigneeAncestry.com DNA, LLC
InventorsJake Kelly Byrnes, Julie M. Granka, Shannon Hateley, Ladan Doroud
Estimating the term…
Disclosed are techniques for characterizing variants of interest and predicting assignments of individuals to communities based on obtained genetic information. To characterize a variant, DNA datasets of reference individuals are accessed and used to generate a cluster with additional individuals. Reference individuals carry a variant at a genetic locus and the additional individuals share IBD with reference individuals. Statistics of genealogical data of the cluster are generated. A result summarizing the characterization of the variant is generated based on the statistics. To determine if an individual belongs to a community, a subset of the individual's haplotypes are inputted into a community-specific model. The model is trained using the training samples that each include haplotypes of reference individuals and a label identifying whether the reference individual belongs to the community. Based on the output of the model, it is determined whether the individual is a member of the community.
A computer-implemented method for using a machine learning network clustering approach to determine a characterization of a target set of one or more genetic variants, the one or more genetic variants being one or more alleles at genetic loci, the computer-implemented method comprising:
A computer-implemented method for using a machine learning network clustering approach to determine a characterization of a target genetic variant, the target genetic variant being an allele at a genetic locus, the computer-implemented method comprising:
Dependencies are inferred from the claim text.