Polymer Sequence Alignment via Signal Quantization
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Solution Overview
Problem
Current methods for determining the relationship between a target sequence and a reference sequence of polymer units, such as in nanopore measurement systems, are computationally expensive and resource-intensive, particularly in the initial stage of estimating the target sequence from measured signals, which hampers speed and efficiency in applications like virus detection and multiplexed sample analysis.
Innovation Solution
A method that segments the measured target signal into quantised signal symbols and compares these with pre-derived reference signal symbols, avoiding the need to model the measurement system for each polymer unit, thereby reducing computational resources and time required for alignment, allowing for faster and more efficient determination of sequence relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the standard technique of estimating the target sequence from measured signals and aligning with reference sequence is used, then alignment accuracy is improved, but computing resources and time are excessively consumed
Solution Approach 1:
The patent segments the continuous measured signal into discrete signal levels through quantization, transforming the complex continuous signal analysis into simpler discrete symbol comparison. This segmentation enables faster processing while maintaining alignment accuracy by preserving the essential information in quantized form.
Solution Approach 2:
The patent changes the parameter representation from continuous signal values to discrete quantized symbols. By transforming the measurement data into a different parameter space (quantized signal levels), the system achieves both computational efficiency and accurate sequence alignment.
2Productivity
If the model-based approach deriving signal levels for each polymer unit is used, then alignment speed is improved, but computational complexity increases
Solution Approach 1:
The patent performs quantization of the measured signal in advance, before the alignment process. This preliminary action transforms the continuous signal into discrete symbols that can be directly compared with reference sequences, eliminating the need for complex model-based signal level derivation during the alignment itself.
Solution Approach 2:
The patent creates a simplified copy of the measured signal in the form of quantized signal symbols. This symbolic representation captures the essential information needed for alignment while being computationally much simpler to handle than the original continuous signal or model-based derivations.
3Measurement precision
If extensive computing resources are allocated for sequence alignment, then analysis accuracy is improved, but cost and resource availability worsen
Solution Approach 1:
The patent uses simple quantized symbols as disposable intermediaries for comparison. These symbolic representations require minimal computational resources to generate and compare, enabling accurate sequence analysis without the need for expensive, resource-intensive modeling and continuous signal processing.
Data Source
AI summary
A relationship (30) between a target sequence of polymer units in a target polymer (10) and a reference sequence of polymer units (20) in a reference polymer such as an alignment is determined from a measured target signal (11) comprising signal levels measured by a measurement system from parts of the target polymer (10) ordered along the target sequence. The measured target signal (10) is segmented, and a sequence of target signal symbols (13) is derived, each representing a quantised signal level derived from the signal levels of a respective segment. A sequence of reference signal symbols (23) representing quantised signal levels of a sequence of modelled reference signal levels predicted by a measurement system model to be measured from the reference sequence of the reference polymer (20) by the measurement system is also used. The sequence of target signal symbols (13) is aligned with the sequence of reference signal symbols (23) to derive the relationship (30) between the target sequence and the reference sequence.