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PLS.R
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args = commandArgs(trailingOnly=TRUE)
if (length(args) == 0){
cat("Syntax: Rscript PLS.R [option: -g (alternative best NNI is selected globally using total LnL), -l (alternative best NNI is selected locally using partition LnL), -m (manually specified trees were compared)] [path to pls_prtlls.csv file] ([path to the tree file])\n")
cat("Example: Rscript PLS.R -g pls_prtlls.csv tree.tre \n")
cat("Example: Rscript PLS.R -m pls_prtlls.csv \n")
quit()
}
library(ape)
library(phangorn)
library(ggtree)
library(ggplot2)
library(grid)
library(gridExtra)
###
opt <- args[1]
tab <- read.csv(args[2], stringsAsFactors=FALSE)
datalist <- data.frame()
if (opt == "-m"){
for (comparison in 3:length(tab[1,])){
dfcomp <- data.frame(char=numeric(),value=numeric())
for (partition in 1:length(tab[,1])){
pls <- tab[partition,2] - tab[partition,comparison]
dfcomp <- rbind(dfcomp, data.frame(char=partition, value=pls))
}
colnames(dfcomp) <- c("char", comparison)
if (length(datalist) == 0){
datalist <- dfcomp
}
else {
datalist <- merge(datalist, dfcomp, by.x="char", by.y="char")
}
}
} else {
start <- read.tree(args[3])
print (start$Nnode)
for (node in 2:start$Nnode){
dfnode <- data.frame(char=numeric(),value=numeric())
tr2 <- (node-1)*2-1
tr3 <- (node-1)*2
print ( paste0 (node,"_", tr2,"_", tr3))
if (opt == "-g"){
if (sum(tab[,tr2+2]) >= sum(tab[,tr3+2])){
nextbesttopo <- tr2
}
else {
nextbesttopo <- tr3
}
}
for (partition in 1:length(tab[,1])){
if (opt == "-l"){
if (sum(tab[partition,tr2+2]) >= sum(tab[partition,tr3+2])){
nextbesttopo <- tr2
}
else {
nextbesttopo <- tr3
}
}
pls <- tab[partition,2] - tab[partition,nextbesttopo+2]
dfnode <- rbind(dfnode, data.frame(char=partition, value=pls))
}
colnames(dfnode) <- c("char", node)
if (length(datalist) == 0){
datalist <- dfnode
}
else {
datalist <- merge(datalist, dfnode, by.x="char", by.y="char")
}
}
}
write.csv(datalist,"pls_datalist.csv",row.names=tab$partition)
#totals
insets <- list()
outlierprts <- numeric()
if (opt == "-m"){
nodelabs <- (3:length(tab[1,]))-1
#print(length(tab[1,]))
#print(nodelabs)
numplots <- 2:(length(tab[1,])-1)
#print(numplots)
outlierall <- data.frame(prt=character(),val=numeric(),node=numeric())
} else {
treeplot <- ggtree(start, size=1) + geom_tiplab(size=2)
nodelabs <- (2+Ntip(start)):(start$Nnode+Ntip(start))
numplots <- 2:start$Nnode
outlierall <- data.frame(prt=character(),val=numeric(),node=numeric(),tips=list())
}
pdf("pls_nodeplots.pdf")
for (i in numplots){
print (i)
datatemp <- datalist[,c(1,i)]
colnames(datatemp) <- c("char", "value")
datatemp$col <- NA
datatemp$col[datatemp$value<0] <- 1
datatemp$col[datatemp$value>=0] <- 0
plot1 <- ggplot(data=datatemp, aes(x=char, y=value, fill=as.character(col)))+
labs(title=nodelabs[i-1])+
geom_bar(stat="identity") + theme(legend.position="none",axis.title.x=element_blank(),
axis.title.y=element_blank(),
axis.ticks.x = element_line(size = 0.1),
axis.ticks.y = element_line(size = 0.1),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = 'white', colour = 'black', size=0.7),
plot.background = element_blank(),
plot.margin = margin(t=1.5, r=2, b=1.5, l=0),
plot.title = element_text(margin = margin(t = 5, b = -10), size=3, colour="red"),
axis.text.x = element_text(size=1,margin = margin(t =0.01), colour = "black"),
axis.text.y = element_text(size=1,margin = margin(t =0.01), colour = "black")) +
scale_fill_manual(values = c("green4","red")) +
scale_x_continuous(breaks=seq(0,length(tab[,1]),10))
plot2 <- ggplot(datatemp, aes(x=1, y=value)) +
geom_boxplot(outlier.shape=NA) +
theme(legend.position="none",axis.title.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.text.x = element_text(size=1,margin = margin(t =0.01), colour = "black"),
axis.ticks.x = element_line(size = 0.1),
axis.ticks.y=element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_rect(fill = 'white', colour = 'black', size=0.7),
plot.background = element_blank(),
plot.margin = margin(t=1.5, r=2, b=1.5, l=0))
print(paste0("node_", i-1, "_outliers_plotN_",nodelabs[i-1]))
###
tempvec <- tab[which(datatemp$value < boxplot(datatemp$value, plot=F)$stats[1]*3),1]
names(tempvec) <- datatemp$value[which(datatemp$value < boxplot(datatemp$value, plot=F)$stats[1]*3)]-boxplot(datatemp$value, plot=F)$stats[1]*3
print(tempvec)
if (length(tempvec) > 0){
for (tv in tempvec){
if (opt == "-m"){
outlierall <- rbind(outlierall, data.frame(prt=tv, val=as.numeric(names(tempvec)[tempvec == tv]), node=nodelabs[i-1]))
} else {
outlierall <- rbind(outlierall, data.frame(prt=tv, val=as.numeric(names(tempvec)[tempvec == tv]), node=nodelabs[i-1], tips=I(list(start$tip.label[unlist(Descendants(start,nodelabs[i-1],"tips"))]))))
}
if (tv %in% names(outlierprts)){
outlierprts[tv] = outlierprts[tv] + 1
}
else{
outlierprts <- c(outlierprts, setNames(1,tv))
}
}
}
###
tempvec <- tab[which(datatemp$value > boxplot(datatemp$value, plot=F)$stats[5]*3),1]
names(tempvec) <- datatemp$value[which(datatemp$value > boxplot(datatemp$value, plot=F)$stats[5]*3)]-boxplot(datatemp$value, plot=F)$stats[5]*3
print(tempvec)
if (length(tempvec) > 0){
for (tv in tempvec){
if (opt == "-m"){
outlierall <- rbind(outlierall, data.frame(prt=tv, val=as.numeric(names(tempvec)[tempvec == tv]), node=nodelabs[i-1]))
} else {
outlierall <- rbind(outlierall, data.frame(prt=tv, val=as.numeric(names(tempvec)[tempvec == tv]), node=nodelabs[i-1], tips=I(list(start$tip.label[unlist(Descendants(start,nodelabs[i-1],"tips"))]))))
}
if (tv %in% names(outlierprts)){
outlierprts[tv] = outlierprts[tv] + 1
}
else{
outlierprts <- c(outlierprts, setNames(1,tv))
}
}
}
insets[[i-1]] <- grid.arrange(plot1, plot2, layout_matrix=matrix(c(1,1,1,2), ncol=4),ncol = 4)
}
dev.off()
names(insets) <- nodelabs
write.csv(sort(outlierprts),"pls_Nnode_outliers.csv")
outlierall$groups <- paste0("N_", outlierall$node, "_", outlierall$prt)
outlierall <- outlierall[order(-abs(outlierall$val)),]
outlierprtsdf <- as.data.frame(outlierprts)
write.csv(outlierall,"pls_LnLdiff_outliers.csv")
ggbar1 <- ggplot(outlierprtsdf, aes(x=reorder(rownames(outlierprtsdf),-outlierprtsdf$outlierprts), y=outlierprtsdf$outlierprts)) +
geom_bar(stat="identity") +
labs(title="Outliers with most nodes", x="Partition", y="Number of nodes with outlier")+
theme(axis.text.x = element_text(angle = 90, hjust = 1))
ggsave("pls_Nnode_outliers.pdf", ggbar1)
ggbar2 <- ggplot(outlierall, aes(x=reorder(outlierall$groups,-abs(outlierall$val)), y=abs(outlierall$val))) +
geom_bar(stat="identity") +
labs(title="Outliers with highest likelihood difference", x="Node and Partition", y="Absolute LnL difference") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
ggsave("pls_LnLdiff_outliers.pdf", ggbar2)
###
if (opt != "-m"){
finalplot <- inset(treeplot, insets, width=max(treeplot$data$x)/10, height=length(treeplot$data$isTip[treeplot$data$isTip])/30,vjust=0.2,hjust=0.005)
ggsave("pls_annotated_tree.pdf",finalplot, width=8.5, height=20)
}