tni.plot.sre {RTN} | R Documentation |
This method plots the results of the subgroup regulon enrichment analysis in a heatmap. The rows of the heatmap represent enriched regulons, while the columns show the subgroups. The plotted values correspond to average regulon activity for a regulon in a subgroup. Enriched values can be marked.
tni.plot.sre(object, nGroupsEnriched = NULL, nTopEnriched = NULL, colors = c("blue","white","red"), breaks = seq(-1.5, 1.5, 0.1), markEnriched = TRUE, ...)
object |
A TNI-class object. |
nGroupsEnriched |
a filter to keep 'nGroupsEnriched' regulons; a single integer specifying how many subgroups a regulon has to be enriched for it to appear in the rows of the heatmap (it must be use either 'nGroupsEnriched' or 'nTopEnriched'). |
nTopEnriched |
a filter to keep 'nTopEnriched' regulons; a single integer specifying how many regulons will be shown for each group. The top regulons are chosen by significance (it must be use either 'nTopEnriched' or 'nGroupsEnriched'). |
colors |
a vector of color for the 'pheatmap'. |
breaks |
a numerical vector of breaks for the 'pheatmap'. |
markEnriched |
a single logical value. If TRUE, asterisks are added to cells of heatmap that were found to be significant. |
... |
parameters passed to 'pheatmap' for customization. |
A heatmap of the subgroup regulon enrichment results.
# load tniData data(tniData) ## Not run: # preprocessing rtni <- tni.constructor(expData=tniData$expData, regulatoryElements=c("PTTG1","E2F2","FOXM1","E2F3","RUNX2"), rowAnnotation=tniData$rowAnnotation) # permutation analysis (infers the reference/relevance network) rtni <- tni.permutation(rtni) # dpi filter (infers the transcriptional network) rtni <- tni.dpi.filter(rtni) #run GSEA2 analysis pipeline rtni <- tni.gsea2(rtni) # set sample groups colAnnotation <- tni.get(rtni, "colAnnotation") sampleGroups <- list(G1=colAnnotation$ID[1:60], G2=colAnnotation$ID[61:90], G3=colAnnotation$ID[91:120]) # run subgroup regulon enrichment analysis rtni <- tni.sre(rtni, sampleGroups) # plot results tni.plot.sre(rtni) ## End(Not run)