# Function that add missing genes to each evidence layer
AddGenes <- function(dataMat, allgenes) {
# ranks genes in each evidence layer ranking (ascending/descending) depends on
# signifType in col4 of dataMat remove duplicated genes in each evidence layer
if (dataMat[1, 4] == "L") {
dataMat <- dataMat[order(dataMat[,3]),]
dataMat <- dataMat[!duplicated(dataMat[, 1]), ]
mat.ranks <- rank(dataMat[, 3], ties.method = "min")
} else if (dataMat[1, 4] == "H") {
dataMat <- dataMat[order(-dataMat[,3]),]
dataMat <- dataMat[!duplicated(dataMat[, 1]), ]
mat.ranks <- rank(-dataMat[, 3], ties.method = "min")
}
dataMat <- cbind(dataMat, mat.ranks)
# missing genes in evidence layer
Genes <- setdiff(allgenes, dataMat[, 1])
Origin <- rep(dataMat[1, 2], length(Genes))
Signif <- rep("NA", length(Genes))
signifType <- rep("NA", length(Genes))
# all missing genes given a single modest rank than all possible ranks
mat.ranks <- rep(length(allgenes) + 1, length(Genes))
add.genes <- data.frame(Genes, Origin, Signif, signifType, mat.ranks)
# add missing genes and ranks to existing evidence layer
dataMat <- rbind(dataMat, add.genes)
dataMat <- dataMat[order(dataMat[, 1]), ]
rank.Mat <- vector()
rank.Mat <- cbind(rank.Mat, as.character(dataMat[, 1]))
rank.Mat <- cbind(rank.Mat, dataMat[, 5])
return(rank.Mat)
}
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