plotEmap: Create EnrichmentMap in Cytoscape to visualize predictive...

In BaderLab/netDx: Network-based patient classifier

Description

Create a network where nodes are predictive pathways passing certain cutoff and edges indicate similarity in gene-sets. Pathways are then clustered to identify themes of predictive pathways. Generates one such network for each patient label.

Usage

plotEmap(
  gmtFile,
  nodeAttrFile,
  netName = "generic",
  scoreCol = "maxScore",
  minScore = 1,
  maxScore = 10,
  nodeFillStops = c(7, 9),
  colorScheme = "cont_heatmap",
  imageFormat = "png",
  verbose = FALSE,
  createStyle = TRUE,
  groupClusters = FALSE,
  hideNodeLabels = FALSE
)

Arguments

gmtFile	(character) file path to GMT file (generated by getEMapInput()). NOTE: This needs to be the absolute path name
nodeAttrFile	(list) file path to nodeAttr.txt file (generated by getEMapInput())
netName	(character) name for network in Cytoscape. Using the patient class name is a good idea. (e.g. SURVIVE_YES and SURVIVE_NO).
scoreCol	(character) column of nodeAttrFile with the node score
minScore	(integer) minimum score of node to show
maxScore	(integer) maximum score of node to show
nodeFillStops	(integer) vector of length 2. Contains score values that indicate "good signal" and "best signal". Nodes with values above "good signal" are coloured orange, and those with "best signal" are coloured red.
colorScheme	(character) colour scheme for nodes. 'cont_heatmap' sets a discrete map ranging from yellow to red for increasing scores. 'netDx_ms' is the colour scheme used in the netDx methods paper. This map is (<=6: white; 7-9: orange; 10: red)
imageFormat	(character) one of PNG, PDF, SVG, or JPEG
verbose	(logical) print messages
createStyle	(logical) if generating more than one EMap, set to TRUE for first one and to FALSE for subsequent. Due to limitation in current version of RCy3
groupClusters	(logical) if TRUE, redraws network with thematic clusters lined up in rows. This setting is useful if setting this flag to FALSE results in a cluttered network. However, applying this layout will organize nodes in each cluster into circles, which loses the c topology.
hideNodeLabels	(logical) if TRUE hides the node label in the EnrichmentMap. Cluster labels remain visible.

Value

No value. Side effect of plotting the EnrichmentMap in an open session of Cytoscape.

Examples

#refer to getEMapInput_many.R for working getEMapInput_many() example
data(featScores)
pathwayList <- readPathways(fetchPathwayDefinitions("October",2020))
pathwayList <- pathwayList[seq_len(5)]
netInfoFile <- system.file("extdata",
	paste("example_output","inputNets.txt",sep=getFileSep()),
	package="netDx")
netTypes <- read.delim(netInfoFile,sep='\t',header=FALSE,as.is=TRUE)
outDir <- paste(tempdir(),'plots',sep=getFileSep())
if (!file.exists(outDir)) dir.create(outDir)
EMap_input <- getEMapInput_many(featScores,pathwayList,
     netTypes,outDir=outDir)
outDir <- paste(getwd(),'plots',sep=getFileSep())
if (!file.exists(outDir)) dir.create(outDir)
gmtFile <- EMap_input[[1]][1]
nodeAttrFile <- EMap_input[[1]][2]

# not run because requires Cytoscape to be installed and open
# plotEmap(gmtFile = gmtFile, nodeAttrFile = nodeAttrFile, 
#\t\tnetName='HighRisk')

BaderLab/netDx documentation built on Sept. 26, 2021, 9:13 a.m.