.loadNetworkFile <- function( networkFile = "inputs/test.net") {
#' Loads the network/topology file.
#'
#' The network file should contain three columns with headers,
#' "Source" "Target" "Type"
#' Here "Source" and "Target" are the names of the genes and "Type" refers to
#' the regulation, "1" if source activates target and "2" if source inhibits
#' target.
#' @param networkFile Network file name
#' @return Network as a dataframe
#'
#'
if(missing(networkFile)){
stop("Please specify the network file!")
}
if(file.exists(networkFile)){
networkTable <- read.table(networkFile, header = TRUE,
stringsAsFactors = FALSE)
colnames(networkTable) <- c("Source","Target","Type")
return(networkTable)
} else {
stop("Network file not found!")
}
}
plotDensity = function(plotData,binCount, plotColor){
colnames(plotData) <- c("x", "y")
h1 <- hist(plotData$x, breaks=binCount, plot=F)
h2 <- hist(plotData$y, breaks=binCount, plot=F)
top <- max(h1$counts, h2$counts)
k <- kde2d(plotData$x, plotData$y, n=binCount)
# margins
oldpar <- par()
par(mar=c(3,3,1,1))
layout(matrix(c(2,0,1,3),2,2,byrow=T),c(3,1), c(1,3))
image(k, col=plotColor, cex = 1, cex.axis = 2, cex.lab = 2, xlab="PC1", ylab="PC2") #plot the image
par(mar=c(0,2,1,0))
barplot(h1$counts, axes=F, ylim=c(0, top), space=0, col='red')
par(mar=c(2,0,0.5,1))
barplot(h2$counts, axes=F, xlim=c(0, top), space=0, col='red', horiz=T)
}
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