Genotype Correlation Assessment Using Ancestry-Stratified Population Data
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Solution Overview
Problem
Current methods for assessing genotype correlations to phenotypes do not adequately account for individual-specific factors such as ancestry, leading to inaccurate predictions of disease susceptibility and treatment responses across different populations.
Innovation Solution
A method and system that generate phenotype profiles by comparing an individual's genomic profile to a database, incorporating ancestry and other specific factors, to provide personalized medical decisions, involving the use of linkage disequilibrium patterns and odds ratios to determine genotype correlations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a genotype correlation study is conducted on a specific population, then the correlation accuracy for that population is improved, but the applicability to other populations deteriorates due to different linkage disequilibrium patterns
Solution Approach 1:
The patent segments the population data by ancestry groups and maintains separate genotype correlation data for different populations. This allows accurate predictions for each specific population while maintaining the ability to serve multiple populations through the segmented database structure.
Solution Approach 2:
The patent applies local quality by using population-specific genotype correlation data tailored to each individual's ancestry. Instead of using a single universal correlation dataset, the system selects and applies correlation data that is locally optimized for the individual's specific population background, thereby improving accuracy for each group.
2Measurement precision
If genotype correlation databases are maintained separately for different populations, then the prediction accuracy for each population is improved, but the system complexity increases
Solution Approach 1:
The patent creates a universal database system that serves multiple populations through a common platform. The system maintains separate correlation data for different populations but manages them through a unified interface and workflow, allowing the same system to serve diverse population groups without requiring separate independent systems for each population.
Solution Approach 2:
The patent introduces an intermediary component that matches individual ancestry information with appropriate population-specific correlation data. This mediator layer handles the complexity of selecting and applying the correct dataset based on individual characteristics, shielding the user from the underlying database complexity while maintaining high prediction accuracy.
3Measurement precision
If ancestry information is incorporated into genotype correlation assessment, then the personalization and accuracy of medical predictions is improved, but the data processing complexity increases
Solution Approach 1:
The patent performs preliminary action by determining an individual's ancestry information before conducting the genotype correlation assessment. This upfront classification allows the system to pre-select the appropriate population-specific correlation data, avoiding the need for complex real-time calculations and simplifying the overall processing workflow.
Solution Approach 2:
The patent uses parameter changes by transitioning from a generic genotype correlation approach to an ancestry-stratified approach. By changing the parameter of population specificity based on ancestry information, the system improves prediction accuracy while managing complexity through structured parameter selection rather than complex computational adjustments.
Data Source
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AI summary
The present disclosure provides methods and systems for assessing an individual's genotype correlations to a phenotype by analyzing the individual's genomic profile and using ancestral data to determine the correlations between genotypes and phenotypes.