Context-Aware Sequence Variant Reconciliation for Consistent Calls
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Solution Overview
Problem
Conventional variant identification techniques produce inconsistent and suboptimal results due to differences in their approaches to identifying variants, leading to the need for either using a single technique that may not be effective for all types of variants or combining multiple techniques that yield inconsistent results, without considering the context of variants at other positions in the sequence data.
Innovation Solution
A system and method for reconciling variant calls by using a statistical model of variant dynamics and performance characteristics to determine a reconciled set of variants, considering variants at multiple positions in the sequence data, and employing techniques like hidden Markov models or minimum cost path algorithms to combine results from multiple variant identification techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple variant identification techniques are used to identify variants, then the coverage of different variant types is improved, but the consistency and reliability of variant calls deteriorate due to inconsistent results from different techniques
Solution Approach 1:
The patent combines results from multiple variant identification techniques by integrating their output into a unified variant call set. This merging process allows the system to leverage the strengths of different techniques (capturing diverse variant types) while resolving inconsistencies through systematic comparison and validation, thus maintaining both versatility and reliability.
Solution Approach 2:
The system employs feedback mechanisms where variant calls from multiple techniques are evaluated against each other and against reference data. Inconsistent calls are identified and resolved through iterative validation, allowing the system to learn from discrepancies and improve the reliability of final variant calls while maintaining comprehensive coverage.
2Reliability
If a single variant identification technique is used, then the consistency of results is maintained, but the ability to identify all types of variants is limited
Solution Approach 1:
The patent implements a universal variant identification system that incorporates multiple specialized techniques, each optimized for different variant types. The system maintains consistency by providing a unified interface and validation framework while achieving versatility through the combined capabilities of the underlying multiple techniques.
3Productivity
If variant calls are made without considering context from other positions, then the processing speed is maintained, but the accuracy of variant identification deteriorates
Solution Approach 1:
The system performs preliminary analysis by examining variants in the context of surrounding positions and sequence data patterns before making final variant calls. This preliminary contextual evaluation is integrated into the processing pipeline in a way that improves accuracy without creating significant bottlenecks, balancing speed and precision.
Data Source
AI summary
Techniques for identifying variations in sequence data relative to reference sequence data. The techniques include accessing information specifying multiple sets of variants in the sequence data relative to reference sequence data, each of the multiple sets of variants being generated by using a respective variant identification technique; and determining, using the information specifying the multiple sets of variants in the sequence data, a reconciled set of variants in the sequence data relative to the reference sequence data, the determining comprising: determining whether a first variant is present at a first position in the sequence data based, at least in part, on one or more variants at one or more other positions in the sequence data.