Phylogenetic clustering (phyloclustering) is an evolutionary
Continuous Time Markov Chain model-based approach to identify
population structure from molecular data without assuming
linkage equilibrium. The package phyclust (Chen 2011) provides a
convenient implementation of phyloclustering for DNA and SNP data,
capable of clustering individuals into subpopulations and identifying
molecular sequences representative of those subpopulations. It is
designed in C for performance, interfaced with R for visualization,
and incorporates other popular open source programs including
ms (Hudson 2002) <doi:10.1093/bioinformatics/18.2.337>,
seq-gen (Rambaut and Grassly 1997)
<doi:10.1093/bioinformatics/13.3.235>,
Hap-Clustering (Tzeng 2005) <doi:10.1002/gepi.20063> and
PAML baseml (Yang 1997, 2007) <doi:10.1093/bioinformatics/13.5.555>,
<doi:10.1093/molbev/msm088>,
for simulating data, additional analyses, and searching the best tree.
See the phyclust website for more information, documentations and
examples.

Phylogenetic clustering (Phyloclustering) is a model-based
approach with the evolution theories and the Continuous Time
Markov Chain theory to identify population structures at the
molecular level without assuming linkage equilibrium. A finite
mixture model optimized by EM algorithms is implemented in C
with varied evolution models, identifiers, initializations and
optimizations. It also includes ms and seq-gen for generate
coalescent trees and sequences, and Hap-Clustering for SNP
sequences. See the phyclust website for more information,
documentations and examples.

c(person("Wei-Chen", "Chen", role = c("aut", "cre"), email =
"wccsnow@gmail.com"), person("Karin", "Dorman", role =
"aut"), person("Yan-Han", "Chen", role = "ctb"))
Wei-Chen Chen [aut, cre],
Karin Dorman [aut],
Yan-Han Chen [ctb]

Phylogenetic clustering (Phyloclustering) is a model-based
approach with the evolution theories and the Continuous Time
Markov Chain theory to identify population structures at the
molecular level without assuming linkage equilibrium. A finite
mixture model optimized by EM algorithms is implemented in C
with varied evolution models, identifiers, initializations and
optimizations. It also includes ms and seq-gen for generate
coalescent trees and sequences, and incorporates Hap-Clustering
for SNP sequences. See the phyclust website for more
information, documentations and examples.