METHODS FOR CELL LABEL CLASSIFICATION

• US 20180127744A1
• Filed: 11/07/2017
• Published: 05/10/2018
• Est. Priority Date: 11/08/2016
• Status: Active Grant

• Current Assignee: Becton, Dickinson & Co
• Original Assignee: Cellular Research, Inc. (Becton, Dickinson & Co)
• Inventors: Hu, Jing, Fan, Christina, Rosenfeld, David, Fan, Jue, Walczak, Elisabeth Marie
• Granted Patent: US 11,608,497 B2
• Time in Patent Office: Days
• CPC Class Codes: C12N 15/1065 Preparation or screening of tagged libraries, e.g. tagged microorganisms by STM-mutagenesis, tagged polynucleotides, gene tags
• CPC Class Codes: C12Q 1/6844 Nucleic acid amplification reactions
• CPC Class Codes: C12Q 1/6851 Quantitative amplification
• CPC Class Codes: C12Q 1/6869 Methods for sequencing
• CPC Class Codes: C12Q 2525/161 incorporating target specific and non-target specific sites
• CPC Class Codes: C12Q 2535/122 Massive parallel sequencing
• CPC Class Codes: C12Q 2537/165 Mathematical modelling, e.g. logarithm, ratio
• CPC Class Codes: C12Q 2561/113 Real time assay
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 45/00 ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks

Abstract

Disclosed herein are methods and systems for classifying cell labels, for example identifying a signal cell label. In some embodiments, the method comprises: obtaining sequencing data of barcoded targets created using targets in cells barcoded using barcodes, wherein a barcode comprises a cell label and a molecular label. After ranking the cell labels, a minimum of a second derivative plot of a cumulative sum plot can be determined. Using the methods, a cell label can be classified as a signal cell label or a noise cell label based on the number of molecular labels with distinct sequences associated with the cell label and a cell label threshold.

Claims

1. A method for identifying a signal cell label, comprising:

(a) barcoding a plurality of targets in a plurality of cells using a plurality of barcodes to create a plurality of barcoded targets, wherein each of the plurality of barcodes comprises a cell label and a molecular label;

(b) obtaining sequencing data of the plurality of barcoded targets;

(c) determining the number of molecular labels with distinct sequences associated with each of the cell labels of the plurality of barcodes;

(d) determining a rank of each of the cell labels of the plurality of barcodes based on the number of molecular labels with distinct sequences associated with each of the cell labels;

(e) generating a cumulative sum plot based on the number of molecular labels with distinct sequences associated with each of the cell labels determined in (c) and the rank of each of the cell labels determined in (d);

(f) generating a second derivative plot of the cumulative sum plot;

(g) determining a minimum of the second derivative plot of the cumulative sum plot, wherein the minimum of the second derivative plot corresponds to a cell label threshold; and

(h) identifying each of the cell labels as a signal cell label or a noise cell label based on the number of molecular labels with distinct sequences associated with each of the cell labels determined in (c) and the cell label threshold determined in (g).

2. The method of claim 1, comprising, if a cell label of the plurality of barcodes is identified as a noise cell label in (h), removing sequencing information associated with the identified cell label from the sequencing data obtained in (b).

3. The method of claim 1, comprising removing sequencing information associated with molecular labels with distinct sequences associated with a target of the plurality of targets from the sequencing data obtained in (b) if the number of the molecular labels with distinct sequences associated with the target of the plurality of targets is above a molecular label occurrence threshold.

4-19. -19. (canceled)

20. A method for determining a signal cell label, comprising:

(a) obtaining sequencing data of a plurality of barcoded targets, wherein the plurality of barcoded targets is created from a plurality of targets in a plurality of cells that are barcoded using a plurality of barcodes, and wherein each of the plurality of barcodes comprises a cell label and a molecular label;

(b) determining a rank of each of the cell labels of the plurality of barcodes based on the number of molecular labels with distinct sequences associated with each of the cell labels of the plurality of barcodes;

(c) determining a cell label threshold based on the number of molecular labels with distinct sequences associated with each of the cell labels and the rank of each of the cell labels of the plurality of barcodes determined in (b); and

(d) identifying each of the cell labels as a signal cell label or a noise cell label based on the number of molecular labels with distinct sequences associated with each of the cell labels and the cell label threshold determined in (c).

21. The method of claim 20, comprising determining the number of molecular labels with distinct sequences associated with each of the cell labels.

22. The method of claim 21, wherein determining the number of molecular labels with distinct sequences associated with each of the cell labels comprises removing sequencing information associated with non-unique molecular labels associated with each of the cell labels from the sequencing data.

23. The method of claim 20, wherein determining the cell label threshold based on the number of molecular labels with distinct sequences associated with each of the cell labels of the plurality of barcodes and the rank of each of the cell labels of the plurality of barcodes determined in (b) comprises:

determining a cumulative sum for each rank of the cell labels, wherein the cumulative sum for the rank comprises a summation of a number of molecular labels with distinct sequences associated with each of the cell labels with a lower rank; and

determining a rank n of the cell labels with the largest change in a cumulative sum for the rank n and a cumulative sum for the next rank n+1, wherein the rank n of the cell labels with the largest change in the cumulative sum and the cumulative sum for the next rank n+1 corresponds to the cell label threshold.

24. The method of claim 20, wherein determining the cell label threshold based on the number of molecular labels with distinct sequences associated with each of the cell labels of the plurality of barcodes comprises:

determining the cell label with the largest change in a cumulative sum for the cell label with a rank n and a cumulative sum for the cell label with the next rank n+1, wherein a number of molecular labels with distinct sequences associated with the cell label corresponds to the cell label threshold.

25. The method of claim 20, wherein determining the cell label threshold based on the number of molecular labels with distinct sequences associated with each of the cell labels of the plurality of barcodes and the rank of each of the cell labels of the plurality of barcodes determined in (b) comprises:

generating a cumulative sum plot based on the number of molecular labels with distinct sequences associated with each of the cell labels and the rank of each of the cell labels determined in (b);

generating a second derivative plot of the cumulative sum plot; and

determining a minimum of the second derivative plot of the cumulative sum plot, wherein the minimum of the second derivative plot corresponds to the cell label threshold.

26. The method of claim 25, wherein generating the cumulative sum plot based on the number of molecular labels with distinct sequences associated with each of the cell labels and the rank of each of the cell labels determined in (b) comprises:

determining a cumulative sum for each rank of the cell labels, wherein the cumulative sum for the rank comprises a summation of a number of molecular labels with distinct sequences associated with each of the cell labels with a lower rank.

27. The method of claim 25, wherein generating the second derivative plot of the cumulative sum plot comprises determining a difference between a cumulative sum of a first rank of the cell labels and a cumulative sum of a second rank of the cell labels over a difference between the first rank and the second rank.

28. The method of claim 27, wherein the difference between the first rank and the second rank is one.

31. The method of claim 20, wherein the cumulative sum plot is a log-log plot.

32. The method of claim 31, wherein the log-log plot is a log₁₀-log₁₀ plot.

33. The method of claim 25, wherein the minimum is a global minimum.

34. The method of claim 25, wherein determining the minimum of the second derivative plot comprises determining a minimum of the second derivative plot above a threshold of a minimum number of molecular labels associated with each of the cell label.

35. The method of claim 34, wherein the threshold of the minimum number of molecular labels associated with each of the cell labels is a percentile threshold.

36. The method of claim 34, wherein the threshold of the minimum number of molecular labels associated with each of the cell labels is determined based on the number of cells in the plurality of cells.

37. The method of claim 25, wherein determining the minimum of the second derivative plot comprises determining a minimum of the second derivative plot below a threshold of a maximum number of molecular labels associated with each of the cell label.

38. The method of claim 37, wherein the threshold of the maximum number of molecular labels associated with each of the cell labels is a percentile threshold.

39. The method of claim 37, wherein the threshold of the maximum number of molecular labels associated with each of the cell labels is determined based on the number of cells in the plurality of cells.

40. The method of claim 20, wherein each of the cell labels is identified as a signal cell label if the number of molecular labels with distinct sequences associated with the each of the cell labels determined is greater than the cell label threshold.

41. The method of claim 20, wherein each of the cell labels is identified as a noise cell label if the number of molecular labels with distinct sequences associated with each of the cell labels determined is not greater than the cell label threshold.

42. The method of claim 20, comprising:

(e) for one or more of the plurality of targets;

(1) counting the number of molecular labels with distinct sequences associated with the target in the sequencing data; and

(2) estimating the number of the target based on the number of molecular labels with distinct sequences associated with the target in the sequencing data counted in (1).

29. (canceled)

30. (canceled)

43. A method for identifying a signal cell label, comprising:

(a) obtaining sequencing data of a plurality of targets of cells, wherein each target is associated with a number of molecular labels with distinct sequences associated with each cell label of a plurality of cell labels;

(b) determining a cell label threshold based on the number of molecular labels with distinct sequences associated with each of the cell labels; and

(c) identifying each of the cell labels as a signal cell label or a noise cell label based on the number of molecular labels with distinct sequences associated with each of the cell labels and the cell label threshold.

44-65. -65. (canceled)

66. A method for identifying a signal cell label, comprising:

(a) barcoding a plurality of targets in a plurality of cells using a plurality of barcodes to create a plurality of barcoded targets, wherein each of the plurality of barcodes comprises a cell label and a molecular label, wherein barcoded targets created from targets of different cells of the plurality of cells have different cell labels, and wherein barcoded targets created from targets of the same cell of the plurality of cells have different molecular labels;

(b) obtaining sequencing data of the plurality of barcoded targets;

(c) determining a feature vector of each cell label of the plurality of barcoded targets, wherein the feature vector comprise numbers of molecular labels with distinct sequences associated with the each cell label;

(d) determining a cluster for the each cell label of the plurality of barcoded targets based on the feature vector; and

(e) identifying the each cell label of the plurality of barcoded targets as a signal cell label or a noise cell label based on a number of cell labels in the cluster and a cluster size threshold.

67-80. -80. (canceled)

81. A method for identifying a signal cell label, comprising:

(a) obtaining sequencing data of a plurality of barcoded targets, wherein the plurality of barcoded targets is create from a plurality of targets in a plurality of cells that are barcoded using a plurality of barcodes, wherein each of the plurality of barcodes comprises a cell label and a molecular label, wherein barcoded targets created from targets of different cells of the plurality of cells have different cell labels, and wherein barcoded targets created from targets of the same cell of the plurality of cells have different molecular labels;

(b) determining a feature vector of each cell label of the plurality of barcoded targets, wherein the feature vector comprise numbers of molecular labels with distinct sequences associated with the each cell label;

(c) determining a cluster for the each cell label of the plurality of barcoded targets based on the feature vector; and

(d) identifying the each cell label of the plurality of barcoded targets as a signal cell label or a noise cell label based on a number of cell labels in the cluster and a cluster size threshold.

82. The method of claim 81, wherein determining the cluster for the each cell label of the plurality of barcoded targets based on the feature vector comprises clustering the each cell label of the plurality of barcoded targets into the cluster based on a distance of the feature vector to the cluster in a feature vector space.

83. The method of claim 81, wherein determining the cluster for the each cell label of the plurality of barcoded targets based on the feature vector comprises:

projecting the feature vector from a feature vector space into a lower dimensional space; and

clustering the each cell label into the cluster based on a distance of the feature vector to the cluster in the lower dimensional space.

84-95. -95. (canceled)

96. A method for identifying a signal cell label, comprising:

(a) obtaining sequencing data of a plurality of first targets of cells, wherein each first target is associated with a number of molecular labels with distinct sequences associated with each cell label of a plurality of cell labels;

(b) identifying each of the cell labels as a signal cell label or a noise cell label based on the number of molecular labels with distinct sequences associated with each of the cell labels and an identification threshold; and

(c) re-identifying at least one of the plurality of cell labels as a signal cell label identified as a noise cell label in (b) or re-identifying at least one of the cell label as a noise cell label identified as a signal cell label in (b).

97-106. -106. (canceled)