Characterization of a Bayesian genetic clustering algorithm based on a Dirichlet process prior and comparison among Bayesian clustering methods

Table 1 Programs provided in this study

Program	Purpose	Assumption	Precedent software equivalent to the program
DPART	Inference of K and assignment of individuals	K and assignment of individuals follow the DP prior	HWLER when λ is fixed to where J_lis the number of alleles at locus l
FUM	Assignment of individuals	Allele frequencies of each population are drawn independently	STRUCTURE (no admixture and no F model)
FCM	Assignment of individuals	Allele frequencies of populations are correlated	STRUCTURE (no admixture and F model)

ISSN: 1471-2105