Sequence Variant Reconciliation Using Multi-Position Call Context
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Solution Overview
Problem
Conventional variant identification techniques produce inconsistent and suboptimal results when applied to sequence data 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.
Innovation Solution
A system that combines multiple sets of variants identified by different variant identification techniques 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 to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple variant identification techniques are used to improve comprehensive variant detection, then the coverage of variant types is improved, but the consistency and reliability of variant calls deteriorates due to differences in their approaches
Solution Approach 1:
The patent combines multiple variant identification techniques (GATK-HC, GATK Unified Genotyper, SAMtools mpileup, FreeBayes, Ion Proton Variant Caller, SNPSVM, and Atlas 2) into a unified framework that processes sequence data through all techniques and reconciles their results. The system merges the outputs of these diverse variant callers by evaluating consistency across techniques and using statistical models to determine reconciled variant calls, thereby maintaining comprehensive coverage while improving reliability through consolidation.
Solution Approach 2:
The patent implements feedback mechanisms where the system evaluates and adjusts variant calls based on consistency across multiple techniques. The reconciled variant set is determined by considering whether variants are supported by multiple techniques and using statistical models to assess confidence. This feedback loop allows the system to refine variant calls by comparing results across different variant identification approaches and adjusting calls based on their consistency.
2Ease of operation
If a single variant identification technique is used to simplify the process, then the ease of operation is improved, but the measurement precision of variant identification deteriorates
Solution Approach 1:
The patent creates a universal variant identification system that can handle multiple variant types (SNPs, insertions, deletions) and multiple sequencing technologies through a single integrated framework. The system universally applies the same reconciliation process across different variant types and techniques, providing multi-functionality that maintains ease of operation while improving precision through comprehensive analysis.
Solution Approach 2:
The patent uses composite approaches by combining multiple variant identification techniques into a unified system that processes sequence data through all techniques and reconciles their results. The system creates a composite variant call assessment that integrates information from different techniques, thereby improving measurement precision while maintaining operational simplicity through a single unified process.
3Productivity
If variant calls are made independently at each position to improve processing speed, then the productivity is improved, but the manufacturing precision of variant identification deteriorates due to lack of contextual information
Solution Approach 1:
The patent performs preliminary actions by pre-processing sequence data and establishing statistical models of variant dynamics before making variant calls. The system prepares contextual information about the sequence context, read depths, and expected variant patterns in advance, allowing for faster processing while maintaining precision. This preliminary preparation enables the system to make informed variant calls without requiring slow, position-by-position analysis.
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.


