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

@inproceedings{Onogi2010CharacterizationOA,
  title={Characterization of a Bayesian genetic clustering algorithm based on a Dirichlet process prior and comparison among Bayesian clustering methods},
  author={Akio Onogi and Masanobu Nurimoto and Mitsuo Morita},
  booktitle={BMC Bioinformatics},
  year={2010}
}
A Bayesian approach based on a Dirichlet process (DP) prior is useful for inferring genetic population structures because it can infer the number of populations and the assignment of individuals simultaneously. However, the properties of the DP prior method are not well understood, and therefore, the use of this method is relatively uncommon. We characterized the DP prior method to increase its practical use. First, we evaluated the usefulness of the sequentially-allocated merge-split (SAMS… CONTINUE READING

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