PathwaysIter: Iterations of the pathway analysis

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

Iterations of the pathway analysis

Description

The MLP method to perform pathway analysis is based on resampling of the data. Therefore it is recommended to perform the pathway analysis multiple times to observe how much the results are influenced by a different resample. The function PathwaysIter performs the pathway analysis as described in Pathways a specified number of times. The input can be one data set or a list as in Pathway.2 and Pathways.

Usage

PathwaysIter(
  List,
  Selection = NULL,
  geneExpr = NULL,
  nrclusters = NULL,
  method = c("limma", "MLP"),
  geneInfo = NULL,
  geneSetSource = "GOBP",
  topP = NULL,
  topG = NULL,
  GENESET = NULL,
  sign = 0.05,
  niter = 10,
  fusionsLog = TRUE,
  weightclust = TRUE,
  names = NULL
)

Arguments

List	A list of clustering outputs or output of theDiffGenes function. The first element of the list will be used as the reference in ReorderToReference. The output of ChooseFeatures is also accepted.
Selection	If pathway analysis should be conducted for a specific selection of objects, this selection can be provided here. Selection can be of the type "character" (names of the objects) or "numeric" (the number of specific cluster). Default is NULL.
geneExpr	The gene expression matrix of the objects. The rows should correspond with the genes.
nrclusters	The number of clusters to cut the dendrogram in. Default is NULL.
method	The method to applied to look for differentially expressed genes and related pathways. For now, only the limma method is available for gene analysis and the MLP method for pathway analysis. Default is c("limma","MLP").
geneInfo	A data frame with at least the columns ENTREZID and SYMBOL. This is necessary to connect the symbolic names of the genes with their EntrezID in the correct order. The order of the gene is here not in the order of the rownames of the gene expression matrix but in the order of their significance. Default is NULL.
geneSetSource	The source for the getGeneSets function ("GOBP", "GOMF","GOCC", "KEGG" or "REACTOME"). Default is "GOBP".
topP	Overrules sign. The number of pathways to display for each cluster. If not specified, only the significant genes are shown. Default is NULL.
topG	Overrules sign. The number of top genes to be returned in the result. If not specified, only the significant genes are shown. Default is NULL.
GENESET	Optional. Can provide own candidate gene sets. Default is NULL.
sign	The significance level to be handled. Default is 0.05.
niter	The number of times to perform pathway analysis. Default is 10.
fusionsLog	Logical. To be handed to ReorderToReference: indicator for the fusion of clusters. Default is TRUE
weightclust	Logical. To be handed to ReorderToReference: to be used for the outputs of CEC, WeightedClust or WeightedSimClust. If TRUE, only the result of the Clust element is considered. Default is TRUE.
names	Optional. Names of the methods. Default is NULL.

Details

This function relies on the suggested Bioconductor packages 'MLP', 'biomaRt' and 'org.Hs.eg.db'.

Value

A list with an element per iteration, each being the output of Pathways.

Examples

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

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)
names=c('FP','TP')

MCF7_Paths_FandT=PathwaysIter(List=L, geneExpr = geneMat, nrclusters = 7, method =
c("limma", "MLP"), geneInfo = GeneInfo, geneSetSource = "GOBP", topP = NULL,
topG = NULL, GENESET = NULL, sign = 0.05,niter=2,fusionsLog = TRUE,
weightclust = TRUE, names =names)

## End(Not run)

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