# US 12,216,110 B2 · Method and system of estimating a sequence of polymer units > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,216,110 B2 - Document ID: US12216110B2 - Status: Granted - Kind: B2 - Application number: 15/487,329 - Filed: 2017-04-13 - Published: 2017-08-03 - Granted: 2025-02-04 - Earliest claimed: 2011-09-23 - Assignees: Oxford Nanopore Technologies PLC - Applicants: Oxford Nanopore Technologies PLC - Inventors: Stuart William Reid; Gavin Harper; Clive Gavin Brown; James Anthony Clarke; Andrew John Heron - Web page: https://patentgrep.com/patent/US12216110B2 ## CPC - G01N 33/48721: {Investigating individual macromolecules, e.g. by translocation through nanopores (Coulter counters in general G01N15/12; fabrication methods for nanoscale apertures B81B1/00; sequencing of nucleic acids C12Q1/68)} - C12Q 1/6869: Methods for sequencing - G01N 27/44791: {Microapparatus (sample containers with integrated microfluidic structures B01L3/5027)} - G01N 33/483: Physical analysis of biological material - G06F 17/18: for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)} - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids - G16B 30/10: Sequence alignment; Homology search - G16B 40/10: Signal processing, e.g. from mass spectrometry [MS] or from PCR - G16B 40/20: Supervised data analysis - G16B 40/30: Unsupervised data analysis - B82Y 15/00: Nanotechnology for interacting, sensing or actuating, e.g. quantum dots as markers in protein assays or molecular motors - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY - B82Y: SPECIFIC USES OR APPLICATIONS OF NANOSTRUCTURES; MEASUREMENT OR ANALYSIS OF NANOSTRUCTURES; MANUFACTURE OR TREATMENT OF NANOSTRUCTURES ## Abstract A sequence of polymer units in a polymer (3), eg. DNA, is estimated from at least one series of measurements related to the polymer, eg. ion current as a function of translocation through a nanopore (1), wherein the value of each measurement is dependent on a k-mer being a group of k polymer units (4). A probabilistic model, especially a hidden Markov model (HMM), is provided, comprising, for a set of possible k-mers: transition weightings representing the chances of transitions from origin k-mers to destination k-mers; and emission weightings in respect of each k-mer that represent the chances of observing given values of measurements for that k-mer. The series of measurements is analysed using an analytical technique, eg. Viterbi decoding, that refers to the model and estimates at least one estimated sequence of polymer units in the polymer based on the likelihood predicted by the model of the series of measurements being produced by sequences of polymer units. In a further embodiment, different voltages are applied across the nanopore during translocation in order to improve the resolution of polymer units. ## Claims ### Claim 1 A computer-implemented method of estimating a sequence of polymer units in a polymer, the method comprising: controlling translocation of the polymer through a nanopore using an enzyme; detecting, using a measurement circuit coupled to electrodes arranged on each side of the nanopore, a sequence of measurements of the polymer, each measurement being indicative of an ion current flowing through the nanopore during said translocation of the polymer through the nanopore; using at least one processor, coupled to a memory, to perform: accessing, in the memory, a probabilistic model comprising, for a set of possible k-mers, wherein a k-mer is a group of k polymer units where k is a positive integer: transition weightings each representing a probability of transition from an origin k-mer to a destination k-mer immediately subsequent in a sequence representing the sequence of polymer units, and wherein, when k is greater than one, transitions to destination k-mers that have a sequence in which the first k-1 polymer units are the same as the last k-1 polymer units of associated origin k-mers have greater probabilities than other transitions; and emission weightings each representing a probability of obtaining given values of ion current measurements for a respective k-mer of the set of possible k-mers; determining likelihoods, for each ion current measurement in the detected sequence of measurements of the polymer, that the ion current measurement was produced by respective k-mers of the set of possible k-mers, by optimizing a sequence of states of the probabilistic model based on the detected sequence of ion current measurements, the transition weightings, and the emission weightings; and determining an estimated sequence of polymer units in the polymer based on the likelihoods determined for each ion current measurement. ### Claim 2 (depends on 1) The method of claim 1, wherein optimizing the sequence of states of the probabilistic model comprises optimization via the Viterbi algorithm. ### Claim 3 (depends on 1) The method of claim 1, wherein the probabilistic model comprises a Hidden Markov Model (HMM). ### Claim 4 (depends on 1) The method of claim 1, wherein the polymer is a polynucleotide. ### Claim 5 (depends on 4) The method of claim 4, wherein translocation of the polynucleotide through the nanopore is assisted by an enzyme. ### Claim 6 (depends on 1) The method of claim 1, wherein the sequence of measurements comprises plural series of measurements each related to said polymer, wherein the value of each measurement is dependent on a k-mer; and wherein determining at least one estimated sequence of polymer units involves treating the plural series of measurements as arranged in plural, respective dimensions. ### Claim 7 (depends on 6) The method of claim 6, wherein each series of measurements are measurements of a same region of the same polymer. ### Claim 8 (depends on 6) The method of claim 6, wherein the plural series of measurements comprise a first series of measurements and a second series of measurements, wherein the first series of measurements are measurements of a first region of a polymer and the second series of measurements are measurements of a second region of a polymer that is related to said first region. ### Claim 9 (depends on 8) The method of claim 8, wherein the first region and the second region are related regions of the same polymer. ### Claim 10 (depends on 8) The method of claim 8, wherein the related regions are complementary. ### Claim 11 (depends on 1) The method of claim 1, wherein providing the probabilistic model comprises accessing, using the at least one processor, the probabilistic model stored in a computer-readable storage medium. ### Claim 12 (depends on 1) The method of claim 1, wherein the nanopore is inserted into a biological membrane, and wherein detecting the sequence of measurements of the polymer comprises measuring a current across the membrane. ### Claim 13 (depends on 1) The method of claim 1, further comprising operating a control circuit to supply a voltage to the electrodes during said translocation of the polymer through the nanopore. ### Claim 14 (depends on 1) The method of claim 1, wherein the enzyme controls a rate of translocation of the polymer through the nanopore throughout said translocation. ### Claim 15 (depends on 1) The method of claim 1, wherein the transition weightings comprise k preferred transitions. ### Claim 16 (depends on 1) The method of claim 1, wherein determining the estimated sequence of polymer units comprises determining an estimated sequence of k-mers and determining the estimated sequence of polymer units based on the estimated sequence of k-mers. ### Claim 17 At least one non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by at least one processor, cause the at least one processor to perform a method of estimating a sequence of polymer units in a polymer, the method comprising: controlling translocation of the polymer through a nanopore using an enzyme; detecting, using a measurement circuit coupled to electrodes arranged on each side of the nanopore, a sequence of measurements of the polymer, each measurement being indicative of an ion current flowing through the nanopore during said translocation of the polymer through the nanopore; using at least one processor, coupled to a memory, to perform: accessing, in the memory, a probabilistic model comprising, for a set of possible k-mers, wherein a k-mer is a group of k polymer units where k is a positive integer: transition weightings each representing a probability of transition from an origin k-mer to a destination k-mer immediately subsequent in a sequence representing the sequence of polymer units, and wherein, when k is greater than one, transitions to destination k-mers that have a sequence in which the first k-1 polymer units are the same as the last k-1 polymer units of associated origin k-mers have greater probabilities than other transitions; and emission weightings each representing a probability of obtaining given values of ion current measurements for a respective k-mer of the set of possible k-mers; determining likelihoods, for each ion current measurement in the detected sequence of measurements of the polymer, that the ion current measurement was produced by respective k-mers of the set of possible k-mers, by optimizing a sequence of states of the probabilistic model based on the detected sequence of ion current measurements, the transition weightings, and the emission weightings; and determining an estimated sequence of polymer units in the polymer based on the likelihoods determined for each ion current measurement. ### Claim 18 A system comprising: at least one processor; and at least one non-transitory computer-readable storage medium having instructions encoded thereon that, when executed by the at least one processor, cause the at least one processor to perform a method of estimating a sequence of polymer units in a polymer, the method comprising: controlling translocation of the polymer through a nanopore using an enzyme; detecting, using a measurement circuit coupled to electrodes arranged on each side of the nanopore, a sequence of measurements of the polymer, each measurement being indicative of an ion current flowing through the nanopore during said translocation of the polymer through the nanopore; using at least one processor, coupled to a memory, to perform: accessing, in the memory, a probabilistic model comprising, for a set of possible k-mers, wherein a k-mer is a group of k polymer units where k is a positive integer: transition weightings each representing a probability of transition from an origin k-mer to a destination k-mer immediately subsequent in a sequence representing the sequence of polymer units, and wherein, when k is greater than one, transitions to destination k-mers that have a sequence in which the first k-1 polymer units are the same as the last k-1 polymer units of associated origin k-mers have greater probabilities than other transitions; and emission weightings each representing a probability of obtaining given values of ion current measurements for a respective k-mer of the set of possible k-mers; determining likelihoods, for each ion current measurement in the detected sequence of measurements of the polymer, that the ion current measurement was produced by respective k-mers of the set of possible k-mers, by optimizing a sequence of states of the probabilistic model based on the detected sequence of ion current measurements, the transition weightings, and the emission weightings; and determining an estimated sequence of polymer units in the polymer based on the likelihoods determined for each ion current measurement.