IntClust (version 0.0.2)

ADEC: Aggregated Data Ensemble Clustering

Description

Function ADEC performs which the functions ADECa, ADECb and ADECc is specified by the user.

Usage

ADEC(List, distmeasure = "tanimoto",normalize=FALSE,method=NULL, t = 10,
r = NULL, nrclusters = NULL, clust = "agnes", linkage = "ward",alpha=0.625
,ResampleFeatures=TRUE)

Arguments

List

A list of data matrices of the same type. It is assumed the rows are corresponding with the objects.

distmeasure

The distance measure to be used on the fused data matrix (character). Should be one of "tanimoto", "euclidean", "jaccard","hamming".

normalize

Logical. Indicates whether to normalize the distance matrices or not. This is recommended if different distance types are used. More details on normalization in Normalization.

method

A method of normalization. Should be one of "Quantile","Fisher-Yates", "standardize","Range" or any of the first letters of these names.

t

The number of iterations.

r

Optional. The number of features to take for the random sample.

nrclusters

The number of clusters to cut the dendrogram in. If a sequence is specified either ADECb or ADECc is performed. A fixed number of clusters defaults to ADECa

clust

Choice of clustering function (character). Defaults to "agnes".

linkage

Choice of inter group dissimilarity (character). Defaults to "ward".

alpha

The parameter alpha to be used in the "flexible" linkage of the agnes function. Defaults to 0.625 and is only used if the linkage is set to "flexible"

ResampleFeatures

Logical. Whether the features should be resamples. If TRUE, either ADECa or ADECc is performed.

Value

The returned value is a list with the following three elements.

AllData

Fused data matrix of the data matrices

S

The resulting co-association matrix

Clust

The resulting clustering

The value has class 'ADEC'. The Clust element will be of interest for further applications.

Details

See the details of ADECa, ADECb and ADEDc for more information.

References

FODEH, J. S., BRANDT, C., LUONG, B. T., HADDAD, A., SCHULTZ, M., MURPHY, T., KRAUTHAMMER, M. (2013). Complementary Ensemble Clustering of Biomedical Data. J Biomed Inform. 46(3) pp.436-443.

See Also

ADECa, ADECb,ADECc

Examples

# NOT RUN {
data(fingerprintMat)
data(targetMat)
L=list(fingerprintMat,targetMat)
MCF7_ADECa=ADEC(L,distmeasure="tanimoto",normalize=FALSE,method=NULL,t=25,r=NULL,
nrclusters=7,clust="agnes",linkage="ward",alpha=0.625,ResampleFeatures=TRUE)
# }