Core Hunter 

Core Hunter is a highly effective and flexible tool for sampling genetic resources from a reference data set and for establishing core subsets.
Core Hunter uses an advanced stochastic local search algorithm for selecting core subsets. Users can specify the sampling intensity and which genetic measures will be used for selection criteria.

Core Hunter is provided with an algorithm capable of selecting core subsets with a high average genetic distance between accessions, or rich genetic diversity overall, or a combination of both. As such it accommodates the formation of diverse types of subsets, either based on breeder’s preferenceres for allele representativeness, or taxonomist’s preferences for allele richness.

Core Hunter is best in finding core subsets with  more genetic diversity and better average genetic distance than the other algorithms for all genetic distance and diversity measures. Core Hunter can attempt to optimize any number of genetic measures simultaneously, based on the preference of the users. In effect, Core Hunter is able to select significantly smaller core subsets, retaining all unique alleles from a reference collection, better than other algorithms.

Documentation and source code for Core Hunter are available at http://corehunter.org/ .

reference:
Thachuk C, Crossa J, Franco J, Dreisigacker S, Warburton M and Davenport GF (2009). Core Hunter: an algorithm for sampling genetic resources based on multiple genetic measures. BMC Bioinformatics 10:243.
DOI: 10.1186/1471-2105-10-243.

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