Computer-assisted analysis
First Claim
1. A method of cell analysis, the method comprising steps of:
- providing cells for analysis;
contacting the cells with at least two agents over a range of titrations;
imaging the cells;
analyzing images of the cells for various visual characteristics;
quantitating the visual characteristics of the cells;
calculating a Kolmogorov-Smirnov statistic for a particular agent, titration, and descriptor as compared to untreated control cells based on a continuous distribution function of the quantitated visual characteristic;
calculating z-scores by normalizing the Kolmogorov-Smirnov statistic for all descriptors and titrations based on the variability of the quantitated visual characteristic;
defining a titration sub-series by shifting the starting point of the titration series over a range of possible shifts;
calculating an s-correlation for each pair of titration sub-series for two agents; and
determining the value of s that yields the highest correlation between two titration subseries.
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Accused Products
Abstract
The present invention provides methods and systems for automated morphological analysis of cells also known as phenotypic screening. The inventive methods are particularly useful in the rapid analysis of cells required in a biological screen or in the screening for agents with a particular mechanism of action. Agents which cause a particular phenotype in the cells can be identified using the inventive quantitative morphometric analysis of cells. The data gathered using the inventive method can also be quantified and analyzed later for various trends and classifications (e.g., Kolmogorov-Smirnov statistics, titration-invariant similarity scores). Characteristics of cells which can be determined using this method include number of nuclei, size of cell, size of nuclei, number of the centrosomes, shape of cells, size of centrosomes, perimeter of nucleus, shape of nucleus, staining for a particular protein, staining for an organelle, pattern of staining, and degree of staining.
18 Citations
20 Claims
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1. A method of cell analysis, the method comprising steps of:
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providing cells for analysis;
contacting the cells with at least two agents over a range of titrations;
imaging the cells;
analyzing images of the cells for various visual characteristics;
quantitating the visual characteristics of the cells;
calculating a Kolmogorov-Smirnov statistic for a particular agent, titration, and descriptor as compared to untreated control cells based on a continuous distribution function of the quantitated visual characteristic;
calculating z-scores by normalizing the Kolmogorov-Smirnov statistic for all descriptors and titrations based on the variability of the quantitated visual characteristic;
defining a titration sub-series by shifting the starting point of the titration series over a range of possible shifts;
calculating an s-correlation for each pair of titration sub-series for two agents; and
determining the value of s that yields the highest correlation between two titration subseries. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method of screening, the method comprising steps of:
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providing a plurality of cell samples;
providing a plurality of test agents;
contacting one of the cell samples with one of the test agents over a range of titrations;
imaging the plurality of cell samples after a time period;
analyzing the images of the cell samples for various visual characteristics (descriptors);
quantitating the data for each descriptor, agent, and titration;
calculating a Kolmogorov-Smirnov statistic for a particular descriptor, agent, and titration as compared to untreated, control cells based on a continuous distribution function;
calculating z-scores by normalizing the Kolmogorov-Smirnov statistic for all sets of descriptors, agents, and titrations based on the variability of the descriptor;
defining a titration sub-series by shifting the starting point of the titration series over a range of possible shifts;
calculating an s-correlation for each pair of titration sub-series for two agents; and
determining the value of s that yields the highest correlation between two titration subseries. - View Dependent Claims (13, 14, 15, 16)
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17. A method of calculating a titration-invariant similarity score, the method comprising steps of:
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providing numerical data quantitating visual characteristics of samples of cells treated with at least two agents;
calculating a Kolmogorov-Smirnov statistic for a particular agent, titration, and descriptor as compared to untreated control cells based on a continuous distribution function of the quantitated visual characteristic;
calculating z-scores by normalizing the Kolmogorov-Smirnov statistic for all descriptors and titrations based on the variability of the quantitated visual characteristic;
defining a titration sub-series by shifting the starting point of the titration series over a range of possible shifts;
calculating an s-correlation for each pair of titration sub-series for two agents; and
determining the value of s that yields the highest correlation between two titration subseries. - View Dependent Claims (18, 19, 20)
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Specification