A new tree-based density kernel with logit-normal splitting probabilities is developed for nonparametric hierarchical mixture models and applied to cluster DNase-seq profiles from ENCODE, yielding clusters aligned with TF binding.
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A tree-based kernel for densities and its applications in clustering DNase-seq profiles
A new tree-based density kernel with logit-normal splitting probabilities is developed for nonparametric hierarchical mixture models and applied to cluster DNase-seq profiles from ENCODE, yielding clusters aligned with TF binding.