ESEA (version 1.0)

PlotRunEnrichment: Plot running Edge enrichment score

Description

Plot running edge enrichment score for the pathway result

Usage

PlotRunEnrichment(EdgeCorScore, PathwayResult, weighted.score.type = 1)

Arguments

EdgeCorScore

A numeric vector. Each element is the differential correlation score of an edge.

PathwayResult

A list of pathway result obtained from the ESEA.main function

weighted.score.type

A value. Edge enrichment correlation-based weighting: 0=no weight, 1=standard weigth, 2 = over-weigth. The default value is 1

Examples

## Not run: 
# 
# #get example data
# dataset<-GetExampleData("dataset")
# class.labels<-GetExampleData("class.labels")
# controlcharactor<-GetExampleData("controlcharactor")
# 
# #get the data for background set of edges
# edgesbackgrand<-GetEdgesBackgrandData()
# 
# #get the edge sets of pathways
# pathwayEdge.db<-GetPathwayEdgeData()
# 
# #calculate the differential correlation score for edges
# EdgeCorScore<-calEdgeCorScore(dataset, class.labels, controlcharactor,edgesbackgrand)
# 
# #identify dysregulated pathways by using the function ESEA.Main
# #Results<-ESEA.Main(EdgeCorScore,pathwayEdge.db)
# Results<-GetExampleData("PathwayResult")
# 
# #obtain the detail results of genes for a significant pathway
# PathwayResult<-Results[[2]][1]
# 
# #Plot running edge enrichment score for the pathway result
# PlotRunEnrichment(EdgeCorScore,PathwayResult,weighted.score.type = 1)
# 
# ## End(Not run)