DetermineWeight_SilClust: Determines an optimal weight for weighted clustering by...

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

Determines an optimal weight for weighted clustering by silhouettes widths.

Description

The function DetermineWeight_SilClust determines an optimal weight for weighted similarity clustering by calculating silhouettes widths. For each given weight, a linear combination of the distance matrices of the single data sources is obtained, medoid clustering is performed and the silhouette widths are regressed against the cluster memberships. A statistic is derived and a p-value obtained via bootstrapping.

Usage

DetermineWeight_SilClust(
  List,
  type = c("data", "dist", "clusters"),
  distmeasure = c("tanimoto", "tanimoto"),
  normalize = c(FALSE, FALSE),
  method = c(NULL, NULL),
  weight = seq(0, 1, by = 0.01),
  nrclusters = NULL,
  names = NULL,
  nboot = 10,
  StopRange = FALSE,
  plottype = "new",
  location = NULL
)

Arguments

List	A list of matrices of the same type. It is assumed the rows are corresponding with the objects.
type	indicates whether the provided matrices in "List" are either data matrices, distance matrices or clustering results obtained from the data. Type should be one of "data", "dist" or "clusters".
distmeasure	A vector of the distance measures to be used on each data matrix. Defaults to c("tanimoto","tanimoto").
normalize	Logical. Indicates whether to normalize the distance matrices. Default is c(FALSE, FALSE).
method	A method of normalization. Default is c(NULL,NULL).
weight	Optional. A list of different weight combinations for the data sets in List. Defaults to seq(0,1,by=0.01).
nrclusters	The number of clusters to cut the dendrogram in. Default is NULL.
names	The labels to give to the elements in List. Default is NULL.
nboot	Number of bootstraps to be run. Default is 10.
StopRange	Logical. Indicates whether the distance matrices with values not between zero and one should be standardized to have so. Default is FALSE.
plottype	Should be one of "pdf","new" or "sweave". Default is "new".
location	If plottype is "pdf", a location should be provided here. Default is NULL.

Value

Two plots and a list with two elements:

Result	A data frame with the statistic for each weight combination
Weight	The optimal weight

.

Examples

## Not run: 
data(fingerprintMat)
data(targetMat)

MCF7_F = Cluster(fingerprintMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="flexible",gap=FALSE,maxK=55,StopRange=FALSE)
MCF7_T = Cluster(targetMat,type="data",distmeasure="tanimoto",normalize=FALSE,
method=NULL,clust="agnes",linkage="flexible",gap=FALSE,maxK=55,StopRange=FALSE)

L=list(MCF7_F,MCF7_T)

MC7_Weight=DetermineWeight_SilClust(List=L,type="clusters",distmeasure=
c("tanimoto","tanimoto"),normalize=c(FALSE,FALSE),method=c(NULL,NULL),
weight=seq(0,1,by=0.01),nrclusters=c(7,7),names=c("FP","TP"),nboot=10,
StopRange=FALSE,plottype="new",location=NULL)

## End(Not run)

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