Variant Calling Accuracy via Non-Random Validation
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Solution Overview
Problem
Next-generation sequencing (NGS) technologies face challenges in variant calling accuracy and reliability due to sequencing errors and platform dependence, leading to higher variant call error rates compared to traditional methods, and random validation may miss significant errors in the NGS sequence.
Innovation Solution
The method involves identifying and validating variants by assessing properties of sequencing reads using a non-random selection criterion and a classifier that combines multiple read properties to enhance accuracy and reliability, leveraging structural and thermodynamic stability of DNA/RNA reads to filter out erroneous variants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If NGS technologies are used to enhance throughput, then productivity is improved, but reliability deteriorates due to higher variant call error rates
Solution Approach 1:
The patent applies preliminary action by performing validation sequencing on selected target portions of the NGS output before final variant calling. This advance validation allows identification and correction of potential errors in the NGS data, thereby improving reliability while maintaining the high throughput advantage of NGS technology.
2Measurement precision
If random validation is performed on NGS output, then some errors are detected, but significant errors may be missed
Solution Approach 1:
The patent applies local quality by implementing a non-random selection criterion that identifies specific target portions of the NGS output for validation based on their individual error probabilities. This allows focused validation on regions most likely to contain errors, improving both error detection capability and validation completeness without requiring validation of the entire dataset.
3Reliability
If Sanger sequencing is used for validation, then reliability is improved, but productivity decreases due to lower throughput
Solution Approach 1:
The patent applies the taking out principle by extracting only the essential validation function from traditional Sanger sequencing and applying it selectively to specific target portions of the NGS output rather than the entire dataset. This maintains the high reliability of Sanger validation while minimizing the impact on overall productivity by validating only a fraction of the data.
4Reliability
If coverage is increased to reduce error rates, then reliability is improved, but sequencing and alignment times increase
Solution Approach 1:
The patent applies partial action by implementing validation sequencing on a selected subset of target portions rather than increasing coverage across the entire NGS output. This provides sufficient validation to reduce error rates in critical regions without the time penalty of high-coverage sequencing across all data, thereby balancing reliability improvement with time efficiency.
Data Source
AI summary
A non-transitory storage medium stores an assembled genetic sequence comprising aligned sequencing reads. An electronic processing device is configured to perform operations including: identifying a possible variant in the assembled genetic sequence; computing value of at least one read property for reads of the assembled genetic sequence; and calling the possible variant conditional upon the computed values of the at least one read property for sequencing reads of the assembled genetic sequence that include the possible variant satisfying an acceptance criterion. The electronic processing device may be further configured to select at least one region of the assembled genetic sequence for validation based on a non random selection criterion.