| eval.stability.clustering {EMA} | R Documentation |
This function compares several clustering methods (link functions and distances) by means of its stability.
eval.stability.clustering(X,nb=c(2:4),f=0.8,nsub=10,s0=0.98,
list_DIS=c("euclidean","pearson"),
list_ALGO=c("average","complete","ward"), pdfname = NULL,
verbose = TRUE)
X |
a data frame with p rows and n columns; if clustering on genes - samples by row and genes by column; if clustering on samples genes by row and samples by column |
nb |
number of classes for partition; it must start at 2 and be sequential(by default 2,3 and 4) |
f |
part of the data set which is randomly picked for each subsample in the resampling procedure (by default 0.8) |
nsub |
half of the number of times the perturbation procedure is applied in the resampling procedure (by default 100) |
list_DIS |
the list of distances to test |
list_ALGO |
the list of linkage method to test |
s0 |
similarity threshold, must lie between 0 and 1 (by default 0.98) |
pdfname |
pdf file name for saving graphic, by default = NULL |
verbose |
print results if verbose = TRUE, by default = TRUE |
Resampling is done by randomly picking without replacement f of the data set; similarity threshold is the value which is pertinent to decide that two partitions are similar; see references
stab.methods |
a list containing methods declared stable for each partition |
Returns a graphic containing the frequencies of methods declared stable
EMA group
http://bioinfo-out.curie.fr/projects/cgh-clustering/index.html
data(marty) ## Test on a smaller dataset ## Not run: example.data<-marty[1:100,] stab<-eval.stability.clustering(example.data) ## End(Not run)