Molecular label counting adjustment methods

Abstract

Disclosed herein are methods and systems for determining the numbers of targets. In some embodiments, the method comprise: stochastically barcoding targets using stochastic barcodes; obtaining sequencing data; for one or more of the targets: counting the number of molecular labels with distinct sequences associated with the target in the sequencing data; identifying clusters of molecular labels of the target using directional adjacency; collapsing the sequencing data using the clusters of molecular labels of the target identified; and estimating the number of the target.

1 .- 14 . (canceled) 
     
     
         15 . A method for determining the numbers of targets, comprising:
 (a) stochastically barcoding a plurality of targets using a plurality of stochastic barcodes to create a plurality of stochastically barcoded targets, wherein each of the plurality of stochastic barcodes comprises a molecular label;   (b) obtaining sequencing data of the stochastically barcoded targets; and   (c) for one or more of the plurality of targets:
 (i) counting the number of molecular labels with distinct sequences associated with the target in the sequencing data; 
 (ii) determining a number of noise molecular labels with distinct sequences associated with the target in the sequencing data; and 
 (iii) estimating the number of the target, wherein the number of the target estimated correlates with the number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i) adjusted according to the number of noise molecular labels determined in (ii). 
   
     
     
         16 . The method of  claim 15 , further comprising determining a sequencing status of the target in the sequencing data. 
     
     
         17 . The method of  claim 16 , wherein the sequencing status of the target in the sequencing data is saturated sequencing, under sequencing, or over sequencing. 
     
     
         18 . The method of  claim 17 , wherein the saturated sequencing status is determined by the target having a number of molecular labels with distinct sequences greater than a predetermined saturation threshold. 
     
     
         19 . (canceled) 
     
     
         20 . (canceled) 
     
     
         21 . The method of  claim 17 , wherein the sequencing status of the target in the sequencing data is the saturated sequencing status, and the number of noise molecular labels determined in (ii) is given a value of zero. 
     
     
         22 . The method of  claim 17 , wherein the under sequencing status is determined by the target having a depth less than a predetermined under sequencing threshold, wherein the depth of the target comprises an average, a minimum, or a maximum depth of the molecular labels with distinct sequences associated with the target in the sequencing data. 
     
     
         23 . (canceled) 
     
     
         24 . The method of  claim 22 , wherein the under sequencing threshold is independent of the number of molecular labels with distinct sequences. 
     
     
         25 . The method of  claim 17 , wherein the sequencing status of the target in the sequencing data is the under sequencing status, and the number of noise molecular labels determined in (ii) is given a value of zero. 
     
     
         26 . The method of  claim 17 , wherein the over sequencing status is determined by the target having a depth greater than a predetermined over sequencing threshold, wherein the depth of the target comprises an average, a minimum, or a maximum depth of the molecular labels with distinct sequences associated with the target in the sequencing data. 
     
     
         27 . (canceled) 
     
     
         28 . The method of  claim 26 , further comprising, when the sequencing status of the target in the sequencing data is the over sequencing status:
 subsampling the number of molecular labels with distinct sequences associated with the target in the sequencing data to about the predetermined over sequencing threshold.   
     
     
         29 . The method of  claim 17 , wherein determining the number of noise molecular labels with distinct sequences associated with the target in the sequencing data comprises:
 when a negative binomial distribution fitting condition is satisfied,
 (iv) fitting a signal negative binomial distribution to the number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i), wherein the signal negative binomial distribution corresponds to a number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i) being signal molecular labels; 
 (v) fitting a noise negative binomial distribution to the number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i), wherein the noise negative binomial distribution corresponds to a number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i) being noise molecular labels; and 
 (vi) determining the number of noise molecular labels using the signal negative binomial distribution fitted in (v) and the noise negative binomial distribution fitted in (vi). 
   
     
     
         30 . The method of  claim 29 , wherein the negative binomial distribution fitting condition comprises: the sequencing status of the target in the sequencing data is not the under sequencing status or the over sequencing status. 
     
     
         31 . The method of  claim 29 , wherein determining the number of noise molecular labels using the signal negative binomial distribution fitted in (v) and the noise negative binomial distribution fitted in (vi) comprises:
 for each of the distinct sequences associated with the target in the sequencing data:
 determining a signal probability of the distinct sequence to be in the signal negative binomial distribution; 
 determining a noise probability of the distinct sequence to be in the noise negative binomial distribution; and 
 determining the distinct sequence to be a noise molecular label when the signal probability is smaller than the noise probability. 
   
     
     
         32 . The method of  claim 17 , wherein determining the number of noise molecular labels with distinct sequences associated with the target in the sequencing data comprises:
 adding pseudopoints to the number of molecular labels with distinct sequences associated with the target in the sequencing data prior to determining the number of noise molecular labels with distinct sequences associated with the target in the sequencing data in (ii) when the sequencing status of the target in the sequencing data is not the under sequencing status or the over sequencing status and the number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i) is less than a pseudopoints threshold.   
     
     
         33 . (canceled) 
     
     
         34 . The method of  claim 17 , wherein determining the number of noise molecular labels with distinct sequences associated with the target in the sequencing data comprises:
 removing non-unique molecular labels when determining the number of noise molecular labels with distinct sequences associated with the target in the sequencing data in (ii) when the sequencing status of the target in the sequencing data is not the under sequencing status or the over sequencing status and the number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (i) is not less than a pseudopoints threshold.   
     
     
         35 . The method of  claim 34 , wherein removing the non-unique molecular labels comprises removing the non-unique molecular labels when determining the number of noise molecular labels with distinct sequences associated with the target in the sequencing data in (ii) when the number of molecular labels with distinct sequences associated with the target in the sequencing data is greater than a predetermined recycled molecular label threshold. 
     
     
         36 . (canceled) 
     
     
         37 . The method of  claim 34 , wherein removing the non-unique molecular labels comprises:
 determining a theoretical number of non-unique molecular labels for the number of molecular labels with distinct sequences associated with the target in the sequencing data; and   removing a molecular label with an occurrence greater than the nth most abundant molecular label of the molecular labels with distinct sequences associated with the target in the sequencing data, wherein n is the theoretical number of non-unique molecular labels.   
     
     
         38 . A computer system for determining the number of targets comprising:
 a hardware processor; and   non-transitory memory having instructions stored thereon, which when executed by the hardware processor cause the processor to perform the method of  claim 15 .   
     
     
         39 .- 126 . (canceled)