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UPGMA and WPGMA clustering. UPGMA (Sokal and Michener 1958) and WPGMA (McQuitty 1966) are a wrapper function around hclust returning a phylo object. supgma perform serial sampled UPGMA similar to Drummond and Rodrigo (2000).

Usage

upgma(D, method = "average", ...)

wpgma(D, method = "mcquitty", ...)

supgma(D, tip.dates, trace = 0, ...)

Arguments

D

A distance matrix, i.e. an object of class dist. If an matrix is supplied it is tried to covert it do a dist object.

method

The agglomeration method to be used. This should be (an unambiguous abbreviation of) one of "ward", "single", "complete", "average", "mcquitty", "median" or "centroid". The default is "average".

...

Further arguments passed to or from other methods.

tip.dates

A named vector of sampling times associated to the tips.

trace

Show output during optimization (see details).

Value

A phylogenetic tree of class phylo.

Details

UPGMA and WPGMA return ultrametric trees, it is implicitly assumed that the distances supplied are close to ultrametric, e.g. hold the molecular clock assumption. Neighbor Joining (NJ) nj and fastME fastme relax this assumption to additive distances. sUPGMA assumes tip dated data.

References

Sneath, P. H., & Sokal, R. R. (1973). Numerical taxonomy. The principles and practice of numerical classification.

Sokal, R. R., & Michener, C. D. (1958). A statistical method for evaluating systematic relationships. University of Kansas Scientific Bulletin, v. 38.

Drummond, A., & Rodrigo, A. G. (2000). Reconstructing genealogies of serial samples under the assumption of a molecular clock using serial-sample UPGMA. Molecular Biology and Evolution, 17(12), 1807-1815.

McQuitty, L.L. (1966). Similarity Analysis by Reciprocal Pairs for Discrete and Continuous Data. Educational and Psychological Measurement, 26, 825–831.

Author

Klaus Schliep klaus.schliep@gmail.com

Examples


data(Laurasiatherian)
dm <- dist.ml(Laurasiatherian)
tree <- upgma(dm)
plot(tree)