Short Variant Detection Using Multi-Flow Sequencing Signals
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Solution Overview
Problem
Existing sequencing methods struggle with high single-signal errors and inefficiency in detecting short genetic variants, particularly due to the high cost and time required by high-depth sequencing to overcome these errors.
Innovation Solution
A method involving sequencing nucleic acid molecules using non-terminating nucleotides in separate nucleotide flows according to a flow-cycle order, generating test sequencing data sets with flow signals, and determining match scores to accurately detect short genetic variants like SNPs and indels, which can be implemented using computer processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-depth sequencing is used to overcome single-signal errors, then variant detection accuracy is improved, but sequencing cost and time increase significantly
Solution Approach 1:
The sequencing process is divided into multiple flow cycles where nucleotides are provided in separate flows (e.g., A-flow, C-flow, G-flow, T-flow). This segmentation allows parallel evaluation of multiple sequence possibilities simultaneously, improving accuracy without requiring proportional increases in total sequencing depth or time.
Solution Approach 2:
The invention transitions from traditional single-signal base calling to a multi-dimensional flow signal analysis. By analyzing signals across multiple flow positions and cycles, the system creates additional dimensions of data that enable more accurate variant detection without increasing sequencing depth.
2Measurement precision
If high-depth sequencing is used to overcome single-signal errors, then variant detection accuracy is improved, but sequencing cost increases
Solution Approach 1:
By segmenting the sequencing process into flows and cycles, the system maximizes the information extracted from each sequencing reaction. This efficient use of sequencing data reduces the total number of reactions needed to achieve high accuracy, thereby reducing reagent and operational costs.
Solution Approach 2:
The invention creates multiple virtual copies of the sequencing data through flow signal analysis. By analyzing the same physical sequencing signal across multiple flow positions and cycles, the system generates redundant information that improves accuracy without requiring additional physical sequencing reactions.
3Ease of operation
If reversible-terminator sequencing-by-synthesis is used, then base calling is simplified, but single-signal errors result in erroneous variant calls
Solution Approach 1:
The system continuously monitors and analyzes flow signals during sequencing, using feedback from each flow cycle to refine the base calling process. By comparing signals across multiple flows and cycles, the system can correct erroneous calls while maintaining operational simplicity.
Solution Approach 2:
The invention adds multiple dimensions to the base calling process by analyzing signals across different flow positions and cycles. This multi-dimensional approach provides additional context that helps distinguish true variants from sequencing errors, improving reliability without complicating the base calling process.
Data Source
AI summary
Methods for detecting a short genetic variant in a test sample are described herein. In some exemplary methods, the short genetic variant is called using one or match scores, which are determined using one or more sequencing data sets obtained from a test nucleic acid molecule, wherein the test sequencing data sets are determined by sequencing the test nucleic acid molecule using non-terminating nucleotides provided in separate nucleotide flows according to a flow-cycle order. Also described herein are methods of sequencing a test nucleic acid molecule using two or more different flow-cycle orders and/or extended flow cycle orders having five or more nucleotide flows per flow cycle.