IntClust (version 0.1.0)

Geneset.intersect: Intersection over resulting gene sets of PathwaysIter function

Description

The function Geneset.intersect collects the results of the PathwaysIter function per method for each cluster and takes the intersection over the iterations per cluster per method. This is to see if over the different resamplings of the data, similar pathways were discovered.

Usage

Geneset.intersect(PathwaysOutput, Selection = FALSE, sign = 0.05,
  names = NULL, seperatetables = FALSE, separatepvals = FALSE)

Arguments

PathwaysOutput

The output of the PathwaysIter function.

Selection

Logical. Indicates whether or not the output of the pathways function were concentrated on a specific selection of objects. If this was the case, Selection should be put to TRUE. Otherwise, it should be put to FALSE. Default is TRUE.

sign

The significance level to be handled for cutting of the pathways. Default is 0.05.

names

Optional. Names of the methods. Default is NULL.

seperatetables

Logical. If TRUE, a separate element is created per cluster containing the pathways for each iteration. Default is FALSE.

separatepvals

Logical. If TRUE, the p-values of the each iteration of each pathway in the intersection is given. If FALSE, only the mean p-value is provided. Default is FALSE.

Value

The output is a list with an element per method. For each method, it is portrayed per cluster which pathways belong to the intersection over all iterations and their corresponding mean p-values.

Examples

# NOT RUN {
# }
# 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)

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)

MCF7_Paths_intersection=Geneset.intersect(PathwaysOutput=MCF7_Paths_FandT,
sign=0.05,names=c("FP","TP"),seperatetables=FALSE,separatepvals=FALSE)

str(MCF7_Paths_intersection)
# }