Fig.S21.EPICON.ghosttree.Rmd

---
title: "Untitled"
author: "Cheng Gao"
date: "4/17/2019"
output: html_document
---


```{r, fig.height = 20, fig.width = 5}
setwd("/Users/chengg/Google\ Drive/EPICON/Mycobiome/Fungal\ ITS/statistic/Total.fungi")
library(ggtree)
library(treeio)

ID0<- read.csv("epicon.ID.2018.08.27.csv")
fung0<-read.csv("epicon.otutable.2018.08.27.csv", head=T, row.names =1) ##Read in the raw data###
fung<-fung0[ID0$AccessionNo!=".",]
ID<-ID0[ID0$AccessionNo!=".",]

fung.ghost <-aggregate(fung, by=list(ID$UniteGhost), FUN=sum, na.rm=TRUE)
row.names(fung.ghost)<-factor(fung.ghost$Group.1); 
fung.ghost1<-data.frame(t(fung.ghost[,-1]))
#fung.ghost1[1:10, 1:10]
species<-colnames(fung.ghost1)
env<-read.csv("epicon.ENV.2018.08.27.csv", head = T)

phylo = read.tree("ghost_tree.nwk")

EPICON.ghost.tree<-drop.tip(phylo,phylo$tip.label[-match(species, phylo$tip.label)])
write.tree(EPICON.ghost.tree, "EPICON.ghost.tree.txt" )

tree.trait<-read.csv("EPICON.GhostTreeTraits.csv", head=T)
tree.trait1<-tree.trait[match(phylo$tip.label, tree.trait$Tips),]
phylo$tip.label==tree.trait1$Tips

lb = EPICON.ghost.tree$tip.label
d = data.frame(label=lb, label2 = tree.trait1$Annot1, phylum = tree.trait1$Phylum)
p1<-ggtree(EPICON.ghost.tree) %<+% d + geom_tiplab(aes(label=label2, color = phylum), size = 1)

pdf("Fig.S21.EPICON.ghosttree.pdf", width=20, height=40)
p1
dev.off()

#########
```