WonM: Weighting on Membership clustering

In MosaiClusteR: An Umbrella Framework for Multi-Source and Multi-Omics Clustering

Weighting on Membership clustering

Description

Weighting on Membership (WonM) is a hierarchy-based consensus technique. Each data matrix is hierarchically clustered and the resulting dendrogram is cut into a range of K values. For every cut a co-membership matrix is built, recording which objects fall in the same cluster. These matrices are averaged within and across data sets to produce an overall consensus matrix, which is transformed into a dissimilarity and clustered a final time.

Usage

WonM(
  List,
  type = c("data", "dist", "clusters"),
  distmeasure = c("tanimoto", "tanimoto"),
  normalize = c(FALSE, FALSE),
  method = c(NULL, NULL),
  nrclusters = list(seq(5, 25), seq(5, 25)),
  clust = "agnes",
  linkage = c("flexible", "flexible"),
  alpha = 0.625
)

Arguments

List	A list of data matrices. It is assumed the rows are corresponding with the objects.
type	Indicates whether the provided matrices in "List" are either data matrices ("data"), distance matrices ("dist") or clustering results obtained from the data ("clusters").
distmeasure	A vector of the distance measures to be used on each data matrix. Should be one of "tanimoto", "euclidean", "jaccard", "hamming". Defaults to c("tanimoto","tanimoto").
normalize	Logical. Indicates whether to normalize the distance matrices or not, defaults to c(FALSE, FALSE) for two data sets. 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. Default is c(NULL,NULL) for two data sets.
nrclusters	A list with, for each data matrix, the sequence of numbers of clusters to cut the dendrogram in. Defaults to list(seq(5,25), seq(5,25)).
clust	Choice of clustering function (character). Defaults to "agnes".
linkage	Choice of inter group dissimilarity (character) for each data set. Defaults to c("flexible", "flexible") for two data sets.
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".

Value

The returned value is a list of two elements:

DistM	The resulting consensus dissimilarity matrix
Clust	The resulting clustering

The value has class 'WonM'.

References

Saeed F., Salim N. and Abdo A. (2012). Voting-based consensus clustering for combining multiple clusterings of chemical structures. Journal of Cheminformatics, 4, 37.

Examples

## Not run: 
data(mosaic_toy)
fit <- WonM(List = mosaic_toy$List, type = "data",
  distmeasure = c("euclidean", "euclidean"), normalize = c(FALSE, FALSE),
  method = c(NULL, NULL), nrclusters = list(seq(3, 6), seq(3, 6)),
  clust = "agnes", linkage = c("ward", "ward"))

## End(Not run)

MosaiClusteR documentation built on Oct. 25, 2026, 1:08 a.m.