Phase-State Model for Sequencing-by-Synthesis Signal Correction
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Solution Overview
Problem
Sequencing-by-synthesis technologies face challenges in accurately estimating signal correction parameters, such as phase synchrony loss and signal droop, which hinder accurate base calling in DNA sequencing.
Innovation Solution
A method and apparatus for estimating signal correction parameters using a phase-state model that simulates nucleotide flows and incorporates signal data from multiple wells to calculate predicted signals, compare them to actual signals, and fit the model to improve signal analysis for base calling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signal correction parameters are estimated using conventional methods, then the base calling process can be performed, but the accuracy of base calling is reduced due to phase synchrony loss and signal droop
Solution Approach 1:
The patent applies preliminary action by estimating signal correction parameters (phase and amplitude correction factors) before performing base calling. The system pre-calculates correction parameters using signal data from multiple wells and nucleotide flow information, then applies these parameters to correct signals before base calling. This preliminary correction of phase synchrony loss and signal droop improves the accuracy of subsequent base calling operations.
Solution Approach 2:
The patent implements feedback by iteratively refining signal correction parameters. The system calculates initial correction parameters, applies them to correct signals, evaluates the corrected signals, and then refines the parameters based on the evaluation results. This feedback loop continues until convergence, ensuring optimal correction parameters are used for base calling, thereby improving both phase synchrony maintenance and base calling accuracy.
2Measurement precision
If signal data from multiple wells is used to estimate correction parameters, then the precision of signal correction improves, but the complexity of the estimation process increases
Solution Approach 1:
The patent applies segmentation by dividing the signal correction process into distinct stages: (1) collecting signal data from multiple wells, (2) estimating phase correction parameters separately from amplitude correction parameters, (3) applying phase correction, and (4) applying amplitude correction. This segmentation of the complex estimation process into manageable steps reduces overall complexity while maintaining high precision through systematic multi-well data analysis.
Solution Approach 2:
The patent implements universality by using signal data from multiple wells for a single comprehensive parameter estimation process. The same set of signal data from multiple wells serves multiple functions: estimating phase correction parameters, estimating amplitude correction parameters, and validating the correction model. This multi-functional use of multi-well data improves signal correction precision without proportionally increasing process complexity.
Data Source
AI summary
A method of estimating a parameter related to sequencing of a sample nucleic acid template includes: receiving signal data relating to nucleotide incorporation events resulting from a series of flows of nucleotides onto an array of wells including (i) a first well containing the sample nucleic acid template and (ii) a plurality of other sample-containing wells; determining sequence information for the sample nucleic acid template using signal data from the first well; and constructing a phase-state model for a set of nucleotide flows that contributed at least in part to the sequence information, wherein the model includes a signal correction parameter that is determined using signal data from the plurality of other sample-containing wells.