Method and apparatus for representing multidimensional data
First Claim
1. A computer-implemented method of generating a vector of values comprising a multi-resolution characterization of flow cytometry data, the method comprising:
- identifying, at a server comprising a memory and a processor, flow data comprising events that describe a quantity of at least a first antibody in an individual cell, wherein the quantity is identified using flow cytometry;
generating a vector of values that characterizes the flow data responsive to iteratively identifying a series of hyperplanes used to segregate the flow data into subsets, wherein at each iteration a hyperplane is independently identified based on a subset of the flow data;
identifying the hyperplane responsive to determining a direction of the maximum variance of the subset of the flow data;
generating a rotated subset of data responsive to rotating the co-ordinates of the subset of the flow data in the direction of the hyperplane;
determining a first value of the rotated subset of the flow data;
splitting the rotated subset of the flow data into two subsets of data according to the first value;
storing the vector of values in the memory; and
uniquely identifying the flow data based on the vector of values.
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Accused Products
Abstract
The present invention relates to methods for representing multidimensional data. The methods of the present invention are well suited but not limited to the representation of multidimensional data in such a way as to enable the comparison and differentiation of data sets. For example, the invention may be applied to the representation of flow cytometric data. The invention further relates to a program storage device having instructions for controlling a computer system to perform the methods, and to a program storage device containing data structures used in the practice of the methods.
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Citations
17 Claims
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1. A computer-implemented method of generating a vector of values comprising a multi-resolution characterization of flow cytometry data, the method comprising:
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identifying, at a server comprising a memory and a processor, flow data comprising events that describe a quantity of at least a first antibody in an individual cell, wherein the quantity is identified using flow cytometry; generating a vector of values that characterizes the flow data responsive to iteratively identifying a series of hyperplanes used to segregate the flow data into subsets, wherein at each iteration a hyperplane is independently identified based on a subset of the flow data; identifying the hyperplane responsive to determining a direction of the maximum variance of the subset of the flow data; generating a rotated subset of data responsive to rotating the co-ordinates of the subset of the flow data in the direction of the hyperplane; determining a first value of the rotated subset of the flow data; splitting the rotated subset of the flow data into two subsets of data according to the first value; storing the vector of values in the memory; and uniquely identifying the flow data based on the vector of values. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer-implemented method of classifying flow cytometry data, the method comprising:
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identifying, at a server comprising a memory and a processor, flow data comprising events that describe a quantity of at least a first antibody in an individual cell, wherein the quantity is identified using flow cytometry; generating a vector of values that characterizes the flow data responsive to iteratively identifying a series of hyperplanes used to segregate the flow data into subsets, wherein at each iteration a hyperplane is identified based on the direction of the maximum variance of a subset of the flow data; generating a rotated subset of data responsive to rotating the co-ordinates of the subset of the flow data in the direction of the hyperplane; determining a first value of the rotated subset of the flow data; splitting the rotated subset of the flow data into two subsets of data according to the first value; storing the vector of values in the memory; and determining whether the flow data belongs to a class based on the vector of values and a template vector that represents the class. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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17. A computer-implemented method of generating a vector of values comprising a multi-resolution characterization of flow cytometry data, the method comprising:
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identifying, at a server comprising a memory and a processor, flow data comprising events that describe a quantity of at least a first antibody in an individual cell, wherein the quantity is identified using flow cytometry; generating a vector of values that characterizes the flow data responsive to iteratively identifying a series of hyperplanes used to segregate the flow data into finer-resolution subsets, wherein at each iteration a hyperplane is independently identified based on a finer-resolution subset of the flow data; identifying the hyperplane responsive to determining a direction of the maximum variance of the subset of the flow data; generating a rotated subset of data responsive to rotating the co-ordinates of the subset of the flow data in the direction of the hyperplane; determining a first median value of the rotated subset of the flow data; splitting the rotated subset of the flow data into two subsets of data according to the first median value; storing the vector of values in the memory; and uniquely identifying the flow data based on the vector of values.
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Specification