Noise reduction methods for nucleic acid and macromolecule sequencing
Inventors
Schuller, Ivan K. • Di Ventra, Massimiliano • Balatsky, Alexander
Assignees
Los Alamos National Laboratory LLC • University of California San Diego UCSD
Publication Number
US-9965586-B2
Publication Date
2018-05-08
Expiration Date
2035-03-20
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Abstract
Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.
Core Innovation
The invention provides methods, systems, and devices for processing macromolecule sequencing data with substantial noise reduction. In particular, it focuses on reducing noise in sequential measurements of macromolecules comprising serial subunits, such as DNA or RNA, by employing cross-correlation of multiple measured signals of a physical property of the subunits. This cross-correlation, including time data associated with the measurements, removes or reduces signal noise that is not in the same frequency and phase as the systematic signal contributions.
The problem being addressed arises from the fact that existing serial physical property sequencing methods, including nanopore and scanning tunneling microscopy (STM) techniques, are highly susceptible to various noise sources. These noise sources, such as thermal motion, electron scattering, and surface atomic rearrangements, significantly degrade the signal-to-noise ratio (SNR) and limit the ability to accurately identify individual subunits like nucleotide bases in nucleic acids. This high noise level makes serial sequencing methods problematic, potentially impossible, without efficient noise reduction.
The core innovation includes a noise reduction scheme applicable to any serial physical property measurement of macromolecules that enables enhanced sequence determination. The methods utilize oversampling and cross-correlation techniques that leverage multiple simultaneous or time-separated measurements with known time delays to filter out noise components uncorrelated in frequency and phase from the systematic signal. Exemplary implementations include stacking multiple nanopore layers or multiple STM measurement tips and using cross-correlated signals to exponentially increase the SNR, allowing cost-efficient, fast, and accurate sequencing of macromolecules including DNA and RNA.
Claims Coverage
The patent includes three independent claims covering methods and systems for processing serial sequencing data acquired using nanopore or scanning tunneling microscopy (STM) systems with noise reduction via cross-correlation techniques.
Noise reduction by cross-correlating measured signals with known timing
The method acquires multiple sequential measurements of physical signals from macromolecule subunits at defined velocity and phase creating known time separations (τ) between measurements. Noise is reduced by cross-correlating these multiple measured signals, including associated time data, to remove or reduce noise not sharing the same frequency and phase with the systematic signal.
Application of cross-correlation noise reduction to sequencing data acquisition systems
The system includes a nanopore or STM data acquisition system capturing multiple measurements of the sequential signal data with known timing, and a computing system processing the sequencing data set by cross-correlating the measured signals and time data to reduce noise related to thermal motion, electron current loss, and atomic rearrangements, generating a noise-reduced data set.
Nanopore system configured for sequential electrical signal measurement with noise reduction
A nanopore system with substrate having nanosized channel and electrode pairs sequentially measures electrical signals of macromolecule subunits translocating through the channel at defined velocity and phase. The system utilizes cross-correlation of multiple sequential signal measurements and time data to reduce noise sources such as thermal motion and localized atomic rearrangements, improving sequence data accuracy.
The independent claims collectively cover methods and systems that utilize multiple time-correlated sequential measurements of macromolecules to cross-correlate signals and remove noise components uncorrelated in frequency and phase. The inventive features focus on reducing sequencing data noise by incorporating known time separations between measurements, thereby enhancing signal-to-noise ratio and enabling more accurate macromolecule sequencing.
Stated Advantages
Increases signal-to-noise ratio (SNR) in serial sequencing data by effectively removing uncorrelated noise components through cross-correlation techniques.
Enables fast, accurate, and cost-efficient determination of macromolecular sequences by improving reliability of serial physical property sequencing methods.
Allows reduction or elimination of noise sources such as thermal motion, electron scattering, and atomic rearrangements during sequencing measurements.
Supports oversampling and multiplexed sequential measurement approaches that statistically enhance measurement significance and sequence identification capability.
Applicable to a range of serial measurement technologies including nanopore and scanning tunneling microscopy methods.
Documented Applications
DNA sequencing, including identifying short DNA fragments and sequencing single DNA bases using nanopore transverse conductance measurements.
Macromolecule sequencing using nanopore systems with electrical current measurement as DNA translocates through a nanopore or nanochannel.
Electronic and structural characterization of nucleic acids and other macromolecules using scanning tunneling microscopy (STM) spectroscopy techniques.
Alternative technologies to standard PCR for sequencing that use electronic and other physical property 'fingerprints'.
Identification of DNA-pathogen interactions and sequencing of other macromolecules such as RNA, peptides, and polymers by serial physical property measurements with improved noise reduction.
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