Description Usage Arguments Details Value Author(s) References Examples
hierarchical clustering function for progeny clustering
1 | hclust.progenyClust(x,k,h.method='ward.D2',dist='euclidean',p=2,...)
|
x |
a numeric matrix, data frame or |
k |
an integer specifying the number of clusters. |
h.method |
the agglomeration method to be used. This should be (an unambiguous abbreviation of) one of |
dist |
the distance measure to be used. This must be one of |
p |
The power of the Minkowski distance, when |
... |
additional arguments in |
The function hclust.progenyClust
mainly streamlines dist
, hclust
and cutree
into one, and structures the output to be directly used by progenyClust
. Most arguments and explanations were kept the same to ensure consistancy and avoid confusion. For more details, please check each individual function.
cluster |
A vector of integers (from 1:k) indicating the cluster membership for each sample. |
tree |
An object of class |
dist |
A dissimilarity structure as produced by |
C.W. Hu, Rice University
Hu, C.W., et al. "Progeny Clustering: A Method to Identify Biological Phenotypes." Scientific reports 5 (2015).
http://www.nature.com/articles/srep12894
1 2 3 4 5 6 7 8 9 10 11 | # a 3-cluster 2-dimensional example dataset
data('test')
# default progeny clsutering
progenyClust(test,FUNclust=hclust.progenyClust,ncluster=2:5)->pc
# plot the scores to select the optimal cluster number
plot(pc)
# plot the clustering results with the optimal cluster number
plot(pc,test)
|
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