Shared DNA Match Differentiation for Reliable Ancestry Trios
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Solution Overview
Problem
Existing direct-to-consumer autosomal DNA testing services struggle to reliably differentiate between Favorable and Unfavorable DNA match trios, leading to inaccurate or incomplete ancestry data reporting, particularly in subscription-based models, without a computationally efficient method to filter shared matches in real-time.
Innovation Solution
The use of Axiomatic Set Theory to evaluate shared DNA match trios through the Shared Match Differentiation (SMD) process, which calculates a Differentiation Value (V) to distinguish between Favorable and Unfavorable trios based on DNA linkage intersections, ensuring accurate genealogical significance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If commercial testing services report all shared matches without differentiation, then the quantity of ancestry data is increased, but the reliability of the data deteriorates due to inclusion of Unfavorable trios
Solution Approach 1:
The patent segments the set of all shared matches into two distinct subsets: Favorable trios (indicating common ancestral origin) and Unfavorable trios (indicating divergent ancestral lines). This segmentation allows the system to report only the reliable Favorable matches while maintaining comprehensive data coverage, thereby improving reliability without sacrificing quantity.
Solution Approach 2:
The patent introduces an intermediary evaluation process using Axiomatic Set Theory and Differentiation Value calculations as a mediator between the raw shared match data and the final ancestry reports. This intermediary layer filters and classifies matches before reporting, ensuring that only reliable Favorable trios are included in ancestry data while maintaining comprehensive coverage.
2Reliability
If a DNA linkage threshold (e.g., 20 centiMorgans) is used to filter shared matches, then the reliability of reported matches is improved, but the quantity of useful data is lost due to suppression of matches below the threshold
Solution Approach 1:
The patent changes the filtering parameter from a fixed DNA linkage threshold (e.g., 20 centiMorgans) to a dynamic Differentiation Value calculation based on Axiomatic Set Theory. This parameter change allows the system to evaluate the genealogical significance of matches without arbitrary threshold constraints, maintaining both reliability and comprehensive data coverage including matches below traditional thresholds.
Solution Approach 2:
The patent transforms the static threshold-based filtering into a dynamic evaluation process that calculates Differentiation Values for each trio based on their specific DNA linkage patterns and set-theoretic properties. This dynamic approach adapts to the specific characteristics of each match relationship, ensuring reliable reporting while preserving useful data that would be lost under fixed thresholds.
3Productivity
If bioinformatic expert systems are used to analyze genetic genealogy problems, then the productivity of ancestry analysis is improved, but the reliability of output verification deteriorates due to lack of independent verification
Solution Approach 1:
The patent implements a feedback mechanism where the Axiomatic Set Theory-based SMD process independently verifies and validates the output of bioinformatic expert systems. The Differentiation Value calculations provide a check on the genealogical significance of matches, allowing the system to self-verify and correct potential errors in bioinformatic analysis, thereby maintaining high productivity while improving reliability through independent verification.
Data Source
AI summary
A bioinformatic system that differentiates collections of shared autosomal DNA (atDNA) matches is disclosed. The invention consists of two main parts: a process which can differentiate “Favourable” Trios of individuals from “Unfavourable” Trios, whilst doing so in a computationally efficient manner, compatible with real-time reporting of DNA testing results; and a desktop/spreadsheet prototype which performs a bioinformatic assessment of three individuals using the matches from their DNA test results by utilizing the aforementioned process. The process may also be applied to assess larger (n-element) collections of individuals, to verify the integrity of datasets produced by other bioinformatic processes, to validate collections of DNA matches used as inputs to bioinformatic processes, and to assess the integrity of ancestral lines connecting individuals of unknown or uncertain pedigree within the context of established family groupings.