## ---- echo = FALSE------------------------------------------------------------ knitr::opts_chunk$set( eval=FALSE ) ## ----------------------------------------------------------------------------- # if(!"RCy3" %in% installed.packages()){ # install.packages("BiocManager") # BiocManager::install("RCy3") # } # library(RCy3) # # if(!"RColorBrewer" %in% installed.packages()){ # install.packages("RColorBrewer") # } # library(RColorBrewer) ## ----------------------------------------------------------------------------- # cytoscapePing() ## ----------------------------------------------------------------------------- # string.cmd = 'string disease query disease="breast cancer" cutoff=0.9 species="Homo sapiens" limit=150' # commandsRun(string.cmd) ## ----------------------------------------------------------------------------- # string.cmd = 'string disease query disease="ovarian cancer" cutoff=0.9 species="Homo sapiens" limit=150' # commandsRun(string.cmd) ## ----------------------------------------------------------------------------- # getNetworkList() ## ----------------------------------------------------------------------------- # layoutNetwork(layout.name='circular') ## ----------------------------------------------------------------------------- # getLayoutNames() ## ----------------------------------------------------------------------------- # getLayoutPropertyNames(layout.name='force-directed') # layoutNetwork('force-directed defaultSpringCoefficient=0.0000008 defaultSpringLength=70') ## ----------------------------------------------------------------------------- # getTableColumnNames('node') ## ----------------------------------------------------------------------------- # disease.score.table <- getTableColumns('node','stringdb::disease score') # disease.score.table ## ----------------------------------------------------------------------------- # par(mar=c(1,1,1,1)) # plot(factor(row.names(disease.score.table)),disease.score.table[,1], ylab=colnames(disease.score.table)[1]) # summary(disease.score.table) ## ----------------------------------------------------------------------------- # top.quart <- quantile(disease.score.table[,1], 0.75) # top.nodes <- row.names(disease.score.table)[which(disease.score.table[,1]>top.quart)] # createSubnetwork(top.nodes,subnetwork.name ='top disease quartile') # #returns a Cytoscape network SUID ## ----------------------------------------------------------------------------- # createSubnetwork(edges='all',subnetwork.name='top disease quartile connected') #handy way to exclude unconnected nodes! ## ----------------------------------------------------------------------------- # setCurrentNetwork(network="STRING network - ovarian cancer") # top.nodes <- row.names(disease.score.table)[tail(order(disease.score.table[,1]),3)] # selectNodes(nodes=top.nodes) # selectFirstNeighbors() # createSubnetwork('selected', subnetwork.name='top disease neighbors') # selected nodes, all connecting edges (default) ## ----------------------------------------------------------------------------- # setCurrentNetwork(network="STRING network - ovarian cancer") # selectNodes(nodes=top.nodes) # commandsPOST('diffusion diffuse') # diffusion! # createSubnetwork('selected',subnetwork.name = 'top disease diffusion') # layoutNetwork('force-directed') ## ----------------------------------------------------------------------------- # load(system.file("extdata","tutorial-ovc-expr-mean-dataset.robj", package="RCy3")) # load(system.file("extdata","tutorial-ovc-mut-dataset.robj", package="RCy3")) # load(system.file("extdata","tutorial-brc-expr-mean-dataset.robj", package="RCy3")) # load(system.file("extdata","tutorial-brc-mut-dataset.robj", package="RCy3")) ## ----------------------------------------------------------------------------- # str(brc.expr) # gene names in row.names of data.frame # str(brc.mut) # gene names in column named 'Hugo_Symbol' ## ----------------------------------------------------------------------------- # setCurrentNetwork(network="STRING network - breast cancer") # layoutNetwork('force-directed') #uses same settings as previously set ## ----------------------------------------------------------------------------- # ?loadTableData # loadTableData(brc.expr,table.key.column = "display name") #default data.frame key is row.names # loadTableData(brc.mut,'Hugo_Symbol',table.key.column = "display name") #specify column name if not default ## ----------------------------------------------------------------------------- # style.name = "dataStyle" # createVisualStyle(style.name) # setVisualStyle(style.name) # # setNodeShapeDefault("ellipse", style.name) #remember to specify your style.name! # setNodeSizeDefault(60, style.name) # setNodeColorDefault("#AAAAAA", style.name) # setEdgeLineWidthDefault(2, style.name) # setNodeLabelMapping('display name', style.name) ## ----------------------------------------------------------------------------- # brc.expr.network = getTableColumns('node','expr.mean') # min.brc.expr = min(brc.expr.network[,1],na.rm=TRUE) # max.brc.expr = max(brc.expr.network[,1],na.rm=TRUE) # data.values = c(min.brc.expr,0,max.brc.expr) ## ----------------------------------------------------------------------------- # display.brewer.all(length(data.values), colorblindFriendly=TRUE, type="div") # div,qual,seq,all # node.colors <- c(rev(brewer.pal(length(data.values), "RdBu"))) ## ----------------------------------------------------------------------------- # setNodeColorMapping('expr.mean', data.values, node.colors, style.name=style.name) ## ----------------------------------------------------------------------------- # brc.mut.network = getTableColumns('node','mut_count') # min.brc.mut = min(brc.mut.network[,1],na.rm=TRUE) # max.brc.mut = max(brc.mut.network[,1],na.rm=TRUE) # data.values = c(min.brc.mut,20,max.brc.mut) # display.brewer.all(length(data.values), colorblindFriendly=TRUE, type="seq") # border.colors <- c(brewer.pal(3, "Reds")) # setNodeBorderColorMapping('mut_count',data.values,border.colors,style.name=style.name) # border.width <- c(2,4,8) # setNodeBorderWidthMapping('mut_count',data.values,border.width,style.name=style.name) ## ----------------------------------------------------------------------------- # top.mut <- (brc.mut$Hugo_Symbol)[tail(order(brc.mut$mut_count),2)] # top.mut # selectNodes(nodes=top.mut,'display name') # commandsPOST('diffusion diffuse') # createSubnetwork('selected',subnetwork.name = 'top mutated diffusion') # layoutNetwork('force-directed') ## ----------------------------------------------------------------------------- # setCurrentNetwork(network="STRING network - ovarian cancer") # clearSelection() # str(ovc.expr) # gene names in row.names of data.frame # str(ovc.mut) # gene names in column named 'Hugo_Symbol' # # loadTableData(ovc.expr, table.key.column = 'display name') # loadTableData(ovc.mut,'Hugo_Symbol', table.key.column = 'display name') ## ----------------------------------------------------------------------------- # setVisualStyle(style.name=style.name) ## ----------------------------------------------------------------------------- # saveSession('tutorial_session') #.cys ## ----------------------------------------------------------------------------- # exportImage(filename='tutorial_image2', type = 'PDF') #.pdf # ?exportImage