Methods of genetic cluster analysis and uses thereof
First Claim
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1. A method of clustering members of a sample, comprising:
- a) applying a hierarchical clustering algorithm to said members of said sample;
b) determining the optimal number of clusters based on the results of said hierarchical clustering algorithm; and
c) distributing said members of said sample into said optimal number of clusters using non-hierarchical clustering.
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Abstract
The present invention is primarily directed to methods of genetic cluster analysis for use in determining the homogeneity and/or heterogeneity of a population or sub-population. Determination of the heterogeneity or homogeneity of a population sample is important in many areas including DNA fingerprinting in forensics and population-based studies such as clinical trials, case-control studies of risk factors, and gene mapping studies.
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Citations
16 Claims
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1. A method of clustering members of a sample, comprising:
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a) applying a hierarchical clustering algorithm to said members of said sample;
b) determining the optimal number of clusters based on the results of said hierarchical clustering algorithm; and
c) distributing said members of said sample into said optimal number of clusters using non-hierarchical clustering. - View Dependent Claims (2, 3, 4, 5)
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6. A computer system for determining clusters of members in a sample, comprising:
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a) First instructions for applying a hierarchical clustering algorithm to said members of said sample;
b) Second instructions for determining the optimal number of clusters based on the results of said hierarchical clustering algorithm; and
c) Third instructions for distributing said members of said sample into said optimal number of clusters using non-hierarchical clustering. - View Dependent Claims (7, 8, 9, 10)
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11. A computer system for clustering members of a sample, comprising:
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a. First instructions for applying a non-hierarchical clustering algorithm to said sample;
b. Second instructions for applying paired-pair analysis to pairs of homozygous pairs in any clusters resulting from said non-hierarchical clustering algorithm to determine whether said non-hierarchical clusters should be further divided; and
c. Third instructions for distribution of said members into additional clusters based on the results of said paired-pair analysis.
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12. A programmed storage device comprising instructions that when executed perform a method for clustering members of a sample, comprising:
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a) applying a hierarchical clustering algorithm to said members of said sample;
b) determining the optimal number of clusters based on the results of said hierarchical clustering algorithm; and
c) distributing said members of said sample into said optimal number of clusters using non-hierarchical clustering. - View Dependent Claims (13, 14, 15, 16)
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Specification