Description Usage Arguments Value Author(s) See Also Examples
View source: R/functions_comp2annot.R
This function allows to cluster samples according to the results of an ICA decomposition. One clustering is run independently for each component.
1 2 3 4 5  clusterSamplesByComp(icaSet, params,
funClus = c("Mclust", "kmeans", "pam", "pamk", "hclust", "agnes"),
filename, clusterOn = c("A", "S"),
level = c("genes", "features"), nbClus,
metric = "euclidean", method = "ward", ...)

icaSet 
An 
params 
A 
funClus 
The function to be used for clustering,
must be one of

filename 
A file name to write the results of the clustering in 
clusterOn 
Specifies the matrix used to apply clustering:

level 
The level of projections to be used when

nbClus 
The number of clusters to be computed,
either a single number or a numeric vector whose length
equals the number of components. If missing (only allowed
if 
metric 
Metric used in 
method 
Method of hierarchical clustering, used in

... 
Additional parameters required by the
clustering function 
A list consisting of three elements
a list specifying the sample clustering for each component,
the complete output of the clustering function,
the function used to perform the clustering.
. When clusterOn="S"
, if some
components were not used because no contributing elements
is selected using the cutoff, the icaSet with the
corresponding component deleted is also returned.
Anne Biton
Mclust
, kmeans
, pam
, pamk
,
hclust
, agnes
, cutree
1 2 3 4 5 6 7 8 9 10 11  data(icaSetCarbayo)
params < buildMineICAParams(resPath="carbayo/", selCutoff=4)
## cluster samples according to their contributions
# using Mclust without a number of clusters
res < clusterSamplesByComp(icaSet=icaSetCarbayo, params=params, funClus="Mclust",
clusterOn="A", filename="clusA")
# using kmeans
res < clusterSamplesByComp(icaSet=icaSetCarbayo, params=params, funClus="kmeans",
clusterOn="A", nbClus=2, filename="clusA")

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