CompareSvsM: Comparison of clustering results for the single and multiple...

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

Comparison of clustering results for the single and multiple source clustering.

Description

The function CompareSvsM plots the comparison of the single source clustering results on the left and that of the multiple source clustering results on the right such that a visual comparison is possible.

Usage

CompareSvsM(
  ListS,
  ListM,
  nrclusters = NULL,
  cols = NULL,
  fusionsLogS = FALSE,
  fusionsLogM = FALSE,
  weightclustS = FALSE,
  weightclustM = FALSE,
  namesS = NULL,
  namesM = NULL,
  margins = c(8.1, 3.1, 3.1, 4.1),
  plottype = "new",
  location = NULL
)

Arguments

ListS	A list of the outputs from the single source clusterings to be compared.
ListM	A list of the outputs from the multiple source clusterings to be compared.
nrclusters	The number of clusters to cut the dendrogram in. Default is NULL.
cols	A character vector with the names of the colours. Default is NULL.
fusionsLogS	The fusionslog parameter for the elements in ListS. Default is FALSE.
fusionsLogM	The fusionsLog parameter for the elements in ListM. Default is FALSE.
weightclustS	The weightclust parameter for the elements in ListS. Default is FALSE.
weightclustM	The weightclust parameter for the elements in ListM. Default is FALSE.
namesS	Optional. Names of the single source clusterings. Default is NULL.
namesM	Optional. Names of the multiple source clusterings. Default is NULL.
margins	Optional. Margins to be used for the plot. Default is c(8.1,3.1,3.1,4.1).
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

A plot with on the left the comparison over the objects in ListS and on the right a comparison over the objects in ListM.

Examples

## Not run: 
data(fingerprintMat)
data(targetMat)
data(Colors1)

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(fingerprintMat,targetMat)

MCF7_W=WeightedClust(List=L,type="data", distmeasure=c("tanimoto","tanimoto"),
normalize=c(FALSE,FALSE),method=c(NULL,NULL),weight=seq(1,0,-0.1),weightclust=0.5
,clust="agnes",linkage="ward",StopRange=FALSE)

ListM=list(MCF7_W)
namesM=seq(1.0,0.0,-0.1)

ListS=list(MCF7_F,MCF7_T)
namesS=c("FP","TP")

CompareSvsM(ListS,ListM,nrclusters=7,cols=Colors1,fusionsLogS=FALSE,
fusionsLogM=FALSE,weightclustS=FALSE,weightclustM=FALSE,namesS,
namesM,plottype="new",location=NULL)

## End(Not run)

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