Method and apparatus for normalization and deconvolution of assay data
First Claim
1. An assay system, comprising:
- at least one type of light scattering particles configured to be bound to an analyte of interest in a sample; and
a scattered light detector configured to analyze analytes in the sample based on detected scattered light of at least first and second colors from the sample.
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Abstract
The present invention is directed to deconvolution and normalization of assay data. The present invention includes a control and analysis system, used in conjunction with a signal generation and detection apparatus, for capturing, processing and analyzing images of samples having resonance light scattering (RLS) particle labels. The control and analysis system processes instructions and algorithms for performing multiplexed assays of two or more colors, for example, to allow separation and analysis of detected light that contains information from two or more different types or sizes of RLS particles. The multiplexing analysis software is preferably incorporated within the system of the present invention, and the multiplexing analysis is preferably performed in real-time during a scanning or assay procedure. The invention provides for a computer readable medium containing instructions for carrying out the same.
137 Citations
65 Claims
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1. An assay system, comprising:
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at least one type of light scattering particles configured to be bound to an analyte of interest in a sample; and
a scattered light detector configured to analyze analytes in the sample based on detected scattered light of at least first and second colors from the sample. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32)
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33. An apparatus for quantifying at least two types of analytes in an assay, said apparatus comprising at least one processor and a memory, wherein said processor is configured to:
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accept spectral intensity data from a sample, wherein said spectral intensity data comprises signals from at least two types of light scattering particle, and wherein a first particle binds to a first analyte and a second particle binds to a second analyte;
convert said spectral intensity data, using multi-spectral deconvolution, into a first intensity that corresponds to an abundance of said first label, and a second intensity that corresponds to an abundance of said second label; and
quantify said first analyte from said first intensity and a concentration of said second analyte from said second intensity. - View Dependent Claims (34, 35, 36, 37)
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38. An analyzer for quantifying at least two types of analytes in multiplexed assays, comprising at least one processor and a memory, wherein said processor is configured to:
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accept spectral image data from a sample that includes two or more spectrally selective images, wherein said spectral image data is comprised of signals from two labels and wherein a first label binds to a first analyte and a second label binds to a second analyte;
convert said two or more spectrally selective images into individual images that either contain only said first label or contain only said second label, using multispectral deconvolution; and
quantify said first analyte by means of particle counting from said individual images that contain only said first label, and said second analyte by means of particle counting from said individual images that contain only said second label.
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39. A method for normalizing assay data, comprising:
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selecting a first population of assay data and a second population of assay data, wherein said first population comprises a dependent set of controls and said second population comprises an independent set of controls;
obtaining a linear relationship between said independent set of controls and said dependent set of controls; and
applying said linear relationship to said first population, thereby producing normalized assay data. - View Dependent Claims (40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 63)
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52. A method of ratiometric analysis, performed on assay data that comprises an array of features, said method comprising:
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selecting a first population of assay data and a second population of assay data, wherein said first population comprises a dependent set of controls and said second population comprises an independent set of controls;
obtaining a linear relationship between said independent set of controls and said dependent set of controls; and
applying said linear relationship to said first population of assay data, thereby producing a first normalized assay data;
obtaining a second linear relationship between said second set of controls and said first set of controls, wherein said first set of controls is treated as an independent variable, and said second set of controls is treated as a dependent variable in said linear relationship. applying said second linear relationship to said second population of assay data, thereby producing a second normalized assay data;
calculating a ratio of a value of said feature in said normalized assay data to a value of said feature in said second normalized assay data; and
identifying said feature as regulated if said ratio exceeds a threshold value. - View Dependent Claims (53, 54)
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55. A method of identifying at least one anomalous feature in assay data, wherein said assay data comprises an array of features, said method comprising:
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dividing the assay data into a first population and a second population, wherein said first population comprises a first set of controls and said second population comprises a second set of controls;
obtaining a first linear relationship between said first set of controls and said second set of controls, including setting one set of controls as a dependent variable and the other set of controls as an independent variable;
obtaining a second linear relationship between said second set of controls and said first set of controls, wherein the control set that is treated as the dependent variable in obtaining said first linear relationship is treated as an independent variable in obtaining said second linear relationship;
applying said first linear relationship to said first population, thereby producing a first normalized assay data;
applying said second linear relationship to said second population, thereby producing a second normalized assay data; and
calculating a first ratio of a value of said feature in said first normalized assay data to a value of said feature in said second normalized assay data; and
calculating a second ratio of a value of said feature in said second normalized assay data to a value of said feature in said first normalized assay data; and
multiplying said first ratio by a reciprocal of said second ratio to produce a product;
identifying said feature as anomalous if said product exceeds a threshold value. - View Dependent Claims (56, 57, 58, 59)
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60. A method for comparing a first set of assay data to a second set of assay data, comprising:
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identifying a first set of controls in said first set of assay data and a second set of controls in said second set of data, wherein said first set of controls and said second set of controls are treated a equivalent;
obtaining a linear relationship between said first set of controls and said second set of controls;
applying said linear relationship to said first set of assay data, thereby transforming said first set of assay data into a third frame of reference;
applying said linear relationship to said second set of assay data, thereby transforming said second set of assay data into said third frame of reference; and
within said third frame of reference, comparing a feature from said first set of assay data that is not in said first set of controls, to a feature from said second set of assay data that is not in said second set of controls.
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61. A method for performing an analyte assay, comprising:
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detecting signals from a plurality of sites from an array format thereby producing assay data;
dividing the assay data into a first population and a second population, wherein said first population comprises a first set of controls and said second population comprises a second set of controls;
obtaining a linear relationship between said first set of controls and said second set of controls;
applying said linear relationship to said assay data, thereby producing normalized assay data; and
correlating said signals to an amount of analyte in each of said sites.
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62. A system for normalizing assay data, comprising:
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a detector that detects signals from discrete areas of said microarray and produces microarray data; and
a computing device having embedded therein a set of instructions to transform said microarray data by;
selecting a first population of assay data and a second population of assay data, wherein said first population comprises a dependent set of controls and said second population comprises an independent set of controls;
obtaining a linear relationship between said independent set of controls and said dependent set of controls; and
applying said linear relationship to said first population, thereby producing normalized assay data.
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64. A computer readable medium having recorded therein a set of instructions for providing normalized microarray data, comprising instructions for:
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selecting a first population of assay data and a second population of assay data, wherein said first population comprises a dependent set of controls and said second population comprises an independent set of controls;
obtaining a linear relationship between said independent set of controls and said dependent set of controls; and
applying said linear relationship to said first population, thereby producing normalized assay data. - View Dependent Claims (65)
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Specification