Copy Number Variant Detection via Self-Normalized Regression
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Solution Overview
Problem
Current methods for determining copy number variants (CNVs) and breakpoints in Anchored Multiplex PCR (AMP) panels require a control baseline or reference, which is not always available, limiting their applicability.
Innovation Solution
A computer-implemented method that receives data representative of primer counts, identifies suitable data for regression modeling, applies kernel change point detection to determine segments, and calculates fold changes relative to a baseline measure without the need for a control baseline.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current CNV methods use control baseline or reference samples for comparison, then measurement precision is improved, but device complexity and loss of time increase due to requiring additional reference samples
Solution Approach 1:
The patent implements self-normalization where the NGS method internally establishes its own baseline from the sequenced data without requiring external control samples. The system uses statistical analysis of the primer count data itself to determine baseline copy numbers, allowing the method to be self-sufficient and eliminate the need for separate reference samples while maintaining detection accuracy
Solution Approach 2:
The patent extracts and removes the requirement for control baseline samples from the CNV detection process. By developing algorithms that can establish baselines from the sample data itself, the method separates the essential function of baseline determination from the problematic dependency on external reference samples, simplifying the overall workflow
2Measurement precision
If current CNV methods require matched normal tissue or cohort panels for normalization, then measurement precision is improved, but loss of time and productivity decrease due to additional sample processing requirements
Solution Approach 1:
The NGS method performs self-normalization by internally establishing baseline copy number expectations from the primer count data without requiring separate normal tissue samples or cohort panels. This self-sufficient approach eliminates the time-consuming process of obtaining and processing additional reference samples while maintaining the ability to calculate accurate fold changes for CNV detection
3Device complexity
If internal self-normalization is used in NGS methods, then device complexity is reduced, but measurement precision deteriorates unless whole genome sequencing data is used
Solution Approach 1:
The patent changes the parameters and statistical approaches used in internal self-normalization to achieve both simplicity and accuracy. By developing sophisticated statistical models that work with targeted sequencing data (rather than requiring whole genome sequencing), the method improves measurement precision while maintaining the simplicity of self-normalization, effectively resolving the trade-off between complexity reduction and accuracy maintenance
Data Source
AI summary
Described herein are methods for determining the number of unique sequence molecules, such as copy number variants and breakpoints, in Anchored Multiplex PCR (AMP) panels using only sequencing data from the sample of interest.