Genotyping Algorithm for Sanger Sequencing Mixed Traces
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Solution Overview
Problem
Current DNA sequencing methods face challenges in accurately genotyping complex loci like the ABO blood group gene, particularly in heterozygous alleles, which can lead to incorrect typing and adverse reactions in organ transplantation and transfusion therapies.
Innovation Solution
A computer-implemented system and method for genotyping that involves obtaining genotyping call data, aligning it with reference sequences, generating numerical scores for allele calls, and making genotyping calls based on match scores using Sanger-based DNA sequencing data and capillary electrophoresis, employing algorithms to improve data accuracy and automate the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Sanger-based DNA sequencing is used for genotyping complex loci like ABO blood group, then the sequencing data can be obtained, but the accuracy of genotyping results deteriorates due to difficulty in deciphering mixed sequencing traces from heterozygous alleles
Solution Approach 1:
The patent segments the complex sequencing trace analysis into distinct computational steps: base calling, quality scoring, heterozygous allele identification, and genotype determination. By dividing the analysis process into manageable segments with specific algorithms for each step, the system can accurately decipher mixed sequencing traces that would be difficult to interpret manually or with simpler methods.
Solution Approach 2:
The patent implements feedback mechanisms through quality scoring systems that evaluate the reliability of base calls and adjust genotyping confidence accordingly. The system uses quality metrics to feedback on the reliability of each base call and adjusts the overall genotype confidence score based on the cumulative quality of evidence, improving accuracy by continuously refining results based on intermediate measurements.
2Productivity
If manual analysis of sequencing traces is used, then flexibility in interpretation is maintained, but productivity deteriorates due to time-consuming analysis process
Solution Approach 1:
The patent implements self-service through automated algorithms that perform base calling, quality assessment, and genotype determination without human intervention. The system uses machine learning models and statistical algorithms to automatically interpret sequencing traces and generate genotyping results, enabling the process to serve itself and eliminating the need for time-consuming manual analysis while maintaining or improving accuracy.
Solution Approach 2:
The patent replaces the mechanical process of manual trace analysis with computational algorithms and automated software systems. By substituting human manual interpretation with computer-based analysis using specialized algorithms for base calling and genotype determination, the system dramatically increases productivity while reducing analysis time from hours or days to minutes or seconds.
3Productivity
If automated algorithms are implemented for genotyping, then productivity is improved, but device complexity increases due to computational requirements
Solution Approach 1:
The patent applies universality by designing a multi-functional computational platform that can handle various genotyping applications (ABO blood group, other complex loci) using the same core algorithms and infrastructure. The system is built to be universally applicable across different genetic analyses, reducing overall complexity by avoiding the need for separate specialized systems for each application while maintaining high productivity through automated processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method enhances the accuracy of genotyping results for complex loci, such as the ABO blood group, by effectively deciphering mixed sequencing traces from heterozygous alleles, ensuring precise matching between donor and recipient in organ transplantation and optimal transfusion therapies.
Implementation Method 1
Capillary electrophoresis is used to separate the extension products resulting from Sanger dideoxy sequencing. During capillary electrophoresis, the molecules are injected by an electrical current into a glass capillary filled with a gel polymer, and an electrical field is applied so that the negatively charged DNA fragments move toward the positive electrode. The speed at which a DNA fragment moves through the capillary medium is inversely proportional to its molecular weight. In practice, the process of capillary electrophoresis can separate the extension products by size at a resolution of one base.
Data Source
AI summary
Methods and systems are provided for genotyping a gene sequence. The method comprises obtaining first genotyping call data representing a query gene sequence. A numerical score is assigned to each of a plurality of allele calls of second genotyping call data by matching the first genotyping call data with the second genotyping call data. the second genotyping call data representing a plurality of candidate gene sequences. A match score is determined for each of the plurality of candidate gene sequences based on the numerical score assigned to each of the plurality of allele calls of the second genotyping call data, and a genotyping call is made for the query gene sequence based on a highest match score from among the match score determined for each of the plurality of candidate gene sequences.