Genetic Variant Identification via IBD Imputation
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Solution Overview
Problem
Current methods face challenges in studying genetic variants of unknown significance (VUS) due to their rarity and the limitations of genotype data from large personal genomic databases, which often lack direct information about specific genetic markers.
Innovation Solution
Implementing imputation-based processing using statistical imputation and Identity by Descent (IBD)-based methods to identify individuals likely to have specific genetic variants, even if the genotype information at those locations is not directly assayed, by constructing haplotype graphs and comparing DNA segments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If genotype data from large personal genomic databases is used, then the quantity of genetic data is increased, but the measurement precision of specific genetic variants is reduced due to lack of direct assay information
Solution Approach 1:
The patent uses Identity by Descent (IBD) segments as an intermediary to connect individuals in the database to variants of interest. Instead of requiring direct assay data for each variant, the system identifies IBD segments that serve as proxies, allowing indirect inference of variant presence while maintaining measurement precision through statistical methods.
Solution Approach 2:
The system creates a copy or representation of variant information through IBD segment matching. Rather than storing or directly measuring every possible variant in the database, it copies the relevant information through identity-by-descent relationships, enabling research on rare variants without direct genotyping of all individuals.
2Measurement precision
If direct assay methods are used for specific genetic variants, then the measurement precision is improved, but the productivity of genetic research is reduced due to inability to study rare variants
Solution Approach 1:
The patent makes the genotype database multi-functional by enabling it to serve both common and rare variant studies through IBD-based imputation. The same database infrastructure that works for common variants is extended to handle rare variants by incorporating IBD segment analysis, eliminating the need for separate research pipelines.
Solution Approach 2:
The system changes the analytical parameters from direct variant calling to IBD segment-based imputation. By shifting from measuring presence/absence of specific variants to measuring shared ancestral segments, the system can detect rare variants that would be impossible to study with traditional direct assay methods.
3Reliability
If IBD-based imputation is implemented, then the ability to detect rare genetic variants is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing IBD segment information in the database during the data ingestion phase. This preliminary processing creates an index of shared segments that can be quickly queried later, avoiding the need for complex real-time computations when researchers want to study specific variants.
Data Source
AI summary
Processing genetic information comprises: receiving an input that includes information pertaining to a specific genetic variant; and identifying, in a database comprising genotype information of a plurality of candidate individuals, a matching individual imputed to have the specific genetic variant. The genotype information of the matching individual corresponding to the specific genetic variant is not directly assayed.