Methods of genetic cluster analysis and uses thereof

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.

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.