Analysis of measurements of a polymer

Abstract

A time-ordered series of measurements of a polymer made during translocation of the polymer through a nanopore are analysed. The measurements are dependent on the identity of k-mers in the nanopore, a k-mer being k polymer units of the polymer, where k is a positive integer. The method involves deriving, from the series of measurements, a feature vector of time-ordered features representing characteristics of the measurements; and determining similarity between the derived feature vector and at least one other feature vector.

1 . A method of analyzing a time-ordered series of measurements of a polymer made during translocation of the polymer through a nanopore, wherein the measurements are dependent on the identity of k-mers in the nanopore, a k-mer being k polymer units of the polymer, where k is a positive integer, the method comprising:
 deriving, from the series of measurements, a feature vector of time-ordered features representing characteristics of the measurements; and   determining similarity between the derived feature vector and at least one other feature vector.   
     
     
         2 . A method according to  claim 1 , wherein the at least one other feature vector is at least one other feature vector stored in a memory in respect of at least one class. 
     
     
         3 . A method according to  claim 2 , wherein the at least one other feature vector stored in the memory is selected depending upon the polymer to be measured. 
     
     
         4 . A method according to  claim 2 , wherein the at least one other feature vector stored in the memory comprises an overall feature vector of a common polymer constructed from the feature vectors of fragments. 
     
     
         5 . A method according to  claim 2 , wherein said step of determining similarity comprises determining similarity between the entirety or part of the derived feature vector and the entirety of the at least one other feature vector stored in the memory. 
     
     
         6 . A method according to  claim 2 , wherein said step of determining similarity comprises determining similarity between the entirety or part of the derived feature vector between the derived feature vector and a part of the at least one other feature vector stored in the memory. 
     
     
         7 . A method according to  claim 2 , further comprising classifying the polymer from which the derived feature vector is derived as belonging to a said class on the basis of the determined similarity. 
     
     
         8 . A method according to  claim 1 , wherein the at least one other feature vector is a feature vector derived using the same method. 
     
     
         9 . A method according to  claim 8 , wherein the at least one other feature vector is plural other feature vectors derived using the same method, and the method further comprises identifying features vectors that are derived from polymers that are fragments of a common polymer on the basis of similarity in overlapping parts of the feature vectors. 
     
     
         10 . A method according to  claim 8 , further comprising constructing an overall feature vector of the common polymer from the feature vectors of the identified fragments. 
     
     
         11 . A method according to  claim 8 , wherein the at least one other feature vector is plural other feature vectors derived using the same method, and the method further comprises identifying clusters of similar feature vectors as a class and classifying the polymers from which the feature vectors are derived as belonging to an identified class. 
     
     
         12 . A method according to  claim 7 , further comprising counting the numbers of feature vectors belonging to different classes. 
     
     
         13 . A method according to  claim 7 , further comprising identifying localized regions where the derived feature vector is dissimilar to a feature vector in respect of the class in which the polymer is classified as belonging. 
     
     
         14 . A method according to  claim 1 , wherein the at least one other feature vector comprises a feature vector stored in a memory and said step of determining similarity comprises determining localized regions where the derived feature vector is dissimilar to the at least one other feature vector stored in the memory. 
     
     
         15 . A method according to  claim 1 , wherein
 groups of consecutive measurements are dependent on a respective k-mer that is different for each group, and   the step of deriving a feature vector comprises identifying groups of consecutive measurements, and, in respect of each group, deriving values of one or more features that represent characteristics of the measurements of the group.   
     
     
         16 . A method according to  claim 1 , wherein the features comprise:
 an average of the group of measurements;   the period of the group of measurements;   a variance of the group of measurements;   asymmetry information;   confidence information of the measurements;   the distribution of the group of measurements; or   any combination thereof.   
     
     
         17 - 21 . (canceled) 
     
     
         22 . A method according to  claim 1 , wherein the polymer is a polynucleotide, and the polymer units are nucleotides. 
     
     
         23 . A method according to  claim 1 , wherein the nanopore is a biological pore. 
     
     
         24 . A method according to  claim 1 , wherein said translocation of the polymer through the nanopore is performed in a ratcheted manner in which successive k-mers are registered with the nanopore. 
     
     
         25 . (canceled) 
     
     
         26 . A method according to  claim 1 , wherein the translocation of the polymer is controlled by a molecular ratchet that is a polymer binding protein. 
     
     
         27 . A method according to  claim 1 , further comprising:
 translocating the polymer through a nanopore; and   making the continuous series of measurements of the polymer.   
     
     
         28 . A method of estimating the presence, absence or amount of a target polymer, the method comprising
 translocating a polymer through a nanopore;   making the continuous series of measurements of the polymer;   analysing the series of measurements using a method according to  claim 1 ; and   estimating the presence, absence or amount of a target polymer based on the analysis.   
     
     
         29 - 35 . (canceled) 
     
     
         36 . A non-transitory computer readable medium storing instructions when executed by a processor to perform a method according to  claim 1 . 
     
     
         37 . An analysis device configured to analyze a time-ordered series of measurements of a polymer made during translocation of the polymer through a nanopore, wherein the measurements are dependent on the identity of k-mers in the nanopore, a k-mer being k polymer units of the polymer, where k is a positive integer, the device comprising:
 means for deriving, from the series of measurements, a feature vector of time-ordered features representing characteristics of the measurements; and   means for determining similarity between the derived feature vector and at least one other feature vector.   
     
     
         38 . A diagnostic device comprising:
 an analysis device according to  claim 37 ; and   a measurement system comprising a nanopore through which a polymer is capable of being translocated, the measurement system being arranged to make a continuous series of measurements of the polymer during translocation.