Methods of genetic cluster analysis and uses thereof
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.
1 . A method of determining the optimal number of clusters of members in a sample, comprising:
a) applying a hierarchical clustering algorithm to said members of said sample; and
b) determining the optimal number of clusters based on the results of said hierarchical clustering algorithm.
2 . The method of claim 1 , wherein said optimal number of clusters is found where the average pairwise intracluster similarity for two parent clusters is larger than the average pairwise intracluster similarity for a new cluster.
3 . A computer system for determining the optimal number of clusters in a sample, comprising:
a) a first module configured to apply a hierarchical clustering algorithm to the members of said sample; and
b) a second module configured to determine the optimal number of clusters based on the results of said hierarchical clustering algorithm.
4 . The computer system of claim 3 , wherein said optimal number of clusters is found where the average pairwise intracluster similarity for two parent clusters is larger than the average pairwise intracluster similarity for a new cluster.
5 . A programmed storage device comprising instructions that when executed perform a method for determining the number of clusters in a sample, comprising:
a) applying a hierarchical clustering algorithm to the members of said sample; and
b) determining the optimal number of clusters based on the results of said hierarchical clustering algorithm.
6 . The programmed storage device of claim 5 , wherein said optimal number of clusters is found where the average pairwise intracluster similarity for two parent clusters is larger than the average pairwise intracluster similarity for a new cluster.