CompareInteractive: Interactive comparison of single and multiple source...

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

Interactive comparison of single and multiple source clustering results

Description

The function CompareInteractive produces an interactive plot of the multiple source clustering results in ListM. By identifying a cluster or a method, a comparison with the single source clustering results in ListS is shown in a new plotting window.

Usage

CompareInteractive(
  ListM,
  ListS,
  nrclusters = NULL,
  cols = NULL,
  fusionsLogM = FALSE,
  fusionsLogS = FALSE,
  weightclustM = FALSE,
  weightclustS = FALSE,
  namesM = NULL,
  namesS = NULL,
  marginsM = c(2, 2.5, 2, 2.5),
  marginsS = c(8, 2.5, 2, 2.5),
  Interactive = TRUE,
  n = 1
)

Arguments

ListM	A list of the outputs from the multiple source clusterings to be compared.
ListS	A list of the outputs from the single 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.
fusionsLogM	The fusionsLog parameter for the elements in ListM. Default is FALSE.
fusionsLogS	The fusionsLog parameter for the elements in ListS. Default is FALSE.
weightclustM	The weightclust parameter for the elements in ListM. Default is FALSE.
weightclustS	The weightclust parameter for the elements in ListS. Default is FALSE.
namesM	Optional. Names of the multiple source clusterings. Default is NULL.
namesS	Optional. Names of the single source clusterings. Default is NULL.
marginsM	Optional. Margins to be used for the ListM plot. Default is c(2,2.5,2,2.5).
marginsS	Optional. Margins to be used for the ListS plot. Default is c(8,2.5,2,2.5).
Interactive	Optional. Do you want an interactive plot? Default is TRUE.
n	The number of methods/clusters you want to identify. Default is 1.

Value

A plot of the comparison of the elements of ListM, on which multiple clusters and/or methods can be identified to compare them to the elements in ListS.

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=c(seq(1.0,0.0,-0.1))

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

CompareInteractive(ListM,ListS,nrclusters=7,cols=Colors1,fusionsLogM=FALSE,
fusionsLogS=FALSE,weightclustM=FALSE,weightclustS=TRUE,namesM,namesS,
marginsM=c(2,2.5,2,2.5),marginsS=c(8,2.5,2,2.5),Interactive=TRUE,n=1)

## End(Not run)

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