PreparePathway: Preparing a data set for pathway analysis
In IntClust: Integration of Multiple Data Sets with Clustering Techniques

Description Usage Arguments Value Examples

The functions for pathway analysis in this package can also work on results of the integrated data functions. However, a differential gene expression needs to be conducted to perform pathway analysis. The function PreparePathway checks if the necessary elements are present in the data structures and if not, the elements such as p-values are created. It is an internal function to all pathway analysis functions but can be used separately as well.

1	PreparePathway(Object, geneExpr, topG, sign)

`Object`	A list with at least an element with the name "objects" such that the function knows which objects to test for differential gene expression. If the elements "Genes" and "pvalsgenes" are present as well, these will be collected and the gene expression is not analyzed.
`geneExpr`	The gene expression matrix or ExpressionSet of the objects. The rows should correspond with the genes.
`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.
`sign`	The significance level to be handled. Default is 0.05.

The returned value is a list with three elements:

`pvalsgenses`	This is a list with that contains a vector of raw p-values for every group of tested objects.
`objects`	This is a list with that contains another list per group of tested objects. Every list contains the lead objects and the ordered objects.
`Genes`	This is a list with that contains contains another list per group of tested objects. Every list contains two data frames, one with information on the top genes and one with information on all genes.

data(fingerprintMat)
data(geneMat)

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


L1=list(MCF7_F)

Comps1=FindCluster(L1,nrclusters=7,select=c(1,1))
Comps2=FindCluster(L1,nrclusters=7,select=c(1,2))
Comps3=FindCluster(L1,nrclusters=7,select=c(1,3))


L2=list()

L2$'Cluster 1'$objects$LeadCpds=Comps1
L2$'Cluster 2'$objects$LeadCpds=Comps2
L2$'Cluster 3'$objects$LeadCpds=Comps2

MCF7_PreparePaths=PreparePathway(Object=L2,geneExpr=geneMat,topG=NULL,sign=0.05)
str(MCF7_PreparePaths)