Nanopore Sequencing Signal Normalization for Baseline Shift Removal
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Solution Overview
Problem
Nanopore-based sequencing chips face challenges due to manufacturing variability and time-dependent non-idealities in measured voltages, leading to inaccuracies in determining nucleotides, which are exacerbated by the use of biochemical circuit elements like lipid bilayers.
Innovation Solution
A signal processing technique that compensates for non-idealities such as zero-point voltage fluctuations and baseline shifts by generating two-dimensional signal values and applying transformations to reduce variance, including a two-dimensional transformation and point-by-point normalization to correct for gain drift and baseline shifts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If signal normalization techniques are applied to compensate for manufacturing variability and time-dependent non-idealities, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies preliminary action by performing normalization and baseline shift removal on sequencing signals before nucleotide identification. The system pre-processes signals to compensate for manufacturing variability and time-dependent non-idealities, establishing a stable baseline that improves subsequent measurement accuracy without requiring complex real-time adjustments
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring signal characteristics and applying dynamic normalization factors. The system measures actual signal drift and baseline shifts, then feeds this information back to adjust normalization parameters, creating a closed-loop system that maintains measurement precision while managing complexity through adaptive rather than static processing
2Measurement precision
If two-dimensional transformation is applied to reduce variance in bright mode data, then measurement precision is improved, but loss of information increases
Solution Approach 1:
The patent applies dimensionality change by transforming one-dimensional bright mode signal values into two-dimensional data points by associating each bright mode value with a corresponding correlated signal value. This dimensional expansion enables variance reduction through geometric transformation while preserving essential signal characteristics, as the transformation operates in a higher-dimensional space where statistical properties can be optimized without discarding information
Data Source
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AI summary
A method of using a sequencing cell (300) includes applying an alternating voltage (328) across the sequencing cell while sequencing a nucleic acid (332), acquiring a plurality of signal values (P(ti)) from the sequencing cell while a tag molecule (338) is threaded in a nanopore (316) of the sequencing cell, and acquiring a plurality of correlated signal values (X(ti)) that are correlated with respective values of the plurality of acquired signal values ( P(ti )) thereby forming a plurality of two-dimensional data points (1201, 1203, 1205, 1207, 1209, 1303, 1305, 1307, 1309, 1311). The two-dimensional data points comprise a first dimension for the acquired signal values and a second dimension for the correlated signal values. The method further includes computing a plurality of transformed signal values by applying a two-dimensional transformation to the two-dimensional data points.