AASK Genetic Match Stratification for Pedigree-Free Ancestral Hierarchies
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Solution Overview
Problem
Existing direct-to-consumer autosomal DNA testing systems struggle to efficiently organize large datasets of genetic matches into meaningful ancestral hierarchies, often requiring user intervention and relying on incomplete or inaccurate pedigrees, which hampers genealogical research.
Innovation Solution
Axiomatic Ancestral Stratification by Kinship (AASK) employs set-theoretic operations to partition and hierarchically organize autosomal DNA matches into subsets sharing a common ancestral line of descent, using meta-classes (alpha, beta, gamma, delta, and epsilon classes) without user input, leveraging the CMA process to refine and extend the utility of genetic complex analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional investigative methodologies are used to organize DNA matches, then user control and flexibility are maintained, but the process becomes hampered by inaccurate pedigrees and requires extensive user intervention
Solution Approach 1:
The system performs self-service by automatically organizing DNA matches into hierarchical structures using set-theoretic operations on the raw match data itself, without requiring user-provided pedigree information. The algorithm independently identifies ancestral lines and creates the organizational structure, making the system self-sufficient and eliminating reliance on potentially inaccurate user input.
Solution Approach 2:
The patent replaces the manual mechanical process of pedigree construction with an automated computational system. Instead of users manually building family trees, the system uses mathematical set operations and algorithms to automatically stratify and organize DNA matches, substituting human effort with automated computational mechanics.
2Loss of information
If CMA process is used to identify common ancestral origins, then comprehensive genetic complex analysis is achieved, but the output collection becomes too large and diffuse for directed investigation
Solution Approach 1:
The system segments the large, diffuse collection of DNA matches into smaller, organized hierarchical groups based on shared ancestral lines. By dividing the comprehensive but unwieldy CMA output into stratified subsets, the system maintains the completeness of the original data while making it manageable for directed genealogical investigation.
Solution Approach 2:
The patent adds a hierarchical dimensional structure to the flat CMA output collection. By organizing matches into multiple levels of ancestry-based groups, the system transforms the two-dimensional data set into a multi-dimensional hierarchical structure, enabling more effective navigation and analysis of the genetic information.
3Adaptability or versatility
If manual pedigree creation by novice researchers is used, then flexibility in documentation is maintained, but the pedigrees are non-existent or inaccurate
Solution Approach 1:
The system replaces the manual mechanical process of pedigree creation with an automated computational algorithm. The algorithm processes raw DNA match data through set-theoretic operations to automatically construct accurate ancestral hierarchies, eliminating the need for manual pedigree documentation while maintaining both accuracy and adaptability.
Solution Approach 2:
The system performs self-service by independently organizing DNA matches into accurate hierarchical structures without requiring user input or manual pedigree creation. The algorithm uses the inherent patterns in the DNA match data itself to construct reliable ancestral relationships, making the system both accurate and adaptable to different research needs.
Data Source
AI summary
A bioinformatic system that identifies the common ancestral origins of minimally correlated autosomal DNA (atDNA) matches is disclosed. The invention consists of three main components: The first is Axiomatic Ancestral Stratification by Kinship (AASK) a process of collating a collection of atDNA matches along ancestral family lines in order to establish a hierarchical sense of their common pedigree. The second is a set of automated scripts, formulae, and data structures to facilitate desktop correlation and tabulation utilizing AASK in conjunction with a desktop spreadsheet program such as Microsoft Excel. The third is a system of data tables and methods to facilitate AASK within a database management system (DBMS) at the enterprise level.