DNA Mixture Deconvolution for Forensic Genealogy
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Solution Overview
Problem
Current forensic genetic genealogy techniques are limited by the need for single-source DNA profiles, as approximately 50% of forensic casework samples are low-level, partially degraded, or mixtures, which cannot be used for investigative genetic genealogy searches due to the inability to deconvolve DNA mixtures without reference profiles.
Innovation Solution
A system and method for deconvolving two-person DNA mixtures into distinct profiles using a series of mathematical steps and machine learning algorithms, enabling distant familial matching and identification without requiring reference DNA profiles, by processing DNA mixtures through a pipeline that includes components for identifying contributors, estimating concentrations, and determining individual DNA profiles for genealogical database searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-source DNA profiles are used for investigative genetic genealogy searches, then identification accuracy is improved, but the applicability to forensic casework samples is worsened because approximately 50% of samples are mixtures that cannot be processed
Solution Approach 1:
The patent segments a mixed DNA profile into multiple individual contributor profiles by identifying and separating distinct genetic signals. The system decomposes the complex mixture data into discrete contributor components, enabling each to be analyzed independently for genealogical matching.
Solution Approach 2:
The patent introduces computational algorithms and statistical models as intermediaries to bridge the gap between mixed DNA profiles and single-source profile requirements. These computational tools act as mediators that transform mixture data into separable contributor profiles suitable for database searching.
2Measurement precision
If reference DNA profiles are required for deconvolution, then contributor identification is improved, but the ability to process unknown mixtures is worsened as many casework samples lack available reference profiles
Solution Approach 1:
The patent enables the DNA mixture itself to provide the information needed for deconvolution without external reference profiles. The system uses internal statistical properties, allele frequency distributions, and computational modeling to extract contributor profiles autonomously from the mixture data.
Solution Approach 2:
The patent transforms the deconvolution approach by changing from reference-dependent parameters to reference-independent statistical parameters. The system uses allele frequencies, genotype probabilities, and mixture ratios as alternative parameters that do not require known reference profiles for analysis.
3Measurement precision
If complex mathematical steps and machine learning algorithms are implemented for deconvolution, then deconvolution accuracy is improved, but system complexity is worsened
Solution Approach 1:
The patent replaces traditional mechanical or manual DNA analysis methods with computational and algorithmic approaches. Machine learning models and statistical software substitute for manual interpretation, automating the deconvolution process while improving accuracy and consistency.
Data Source
AI summary
This patent application relates generally to mixture deconvolution systems and methods for identifying DNA profiles. Various embodiments of the present invention concern the deconvolution of unknown DNA profiles in a two-person DNA mixture into two DNA profiles. Deconvolution methods isolate distinct DNA profiles from a DNA mixture without the need to match against DNA reference profiles. Various embodiments include a mixture deconvolution pipeline that involves a series of mathematical steps and machine learning algorithms to achieve the desired performance and decision-support outputs. Various embodiments enable distant familial matching to existing investigative genetic genealogy (IGG; also known as forensic genetic genealogy (FGG)) databases. This capability enables the generation of investigative leads from unresolved casework samples (i.e., DNA mixtures) by identifying possible genealogical relationships to one or more person(s) of interest. Such aspects may be performed in association with one or more systems used for genetic identification.