upgma | R Documentation |
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).
upgma(D, method = "average", ...)
wpgma(D, method = "mcquitty", ...)
supgma(D, tip.dates, trace = 0, ...)
D |
A distance matrix, i.e. an object of class |
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). |
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.
A phylogenetic tree of class phylo
.
Klaus Schliep klaus.schliep@gmail.com
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.
hclust
, dist.hamming
, NJ
,
as.phylo
, fastme
,
nnls.tree
, rtt
data(Laurasiatherian)
dm <- dist.ml(Laurasiatherian)
tree <- upgma(dm)
plot(tree)
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