PCA analysis of rhizosphere effect.Rmd

---
title: "PCA analysis of rhizosphere effect"
author: "xyz"
date: "2019/12/11"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(root.dir="/media/sf_bigData/rootChamberWheat")
```

```{r}
# df<-read.table("X101SC19050239-Z01-F001-B1-41_result/02.OTUanalysis/taxa_abundance/Absolute/otu_table.txt")
df<-read.table("X101SC19050239-Z01-F001-B1-41_result/02.OTUanalysis/taxa_abundance/Relative/otu_table.relative.xls")
metaData<-readxl::read_xlsx("metaData.xlsx")
```

[draw neat polygons around scatterplot regions in ggplot2](https://stats.stackexchange.com/questions/22805/how-to-draw-neat-polygons-around-scatterplot-regions-in-ggplot2)

```{r}
library(vegan)
library(ggplot2)
library(ggrepel)

# group by CKR CKN CKF
otu<-t(df[,2:55])
Treatments<-factor(paste0(metaData$Fertilizer,metaData$Position),levels=c("CKR","CKN","CKF","UR","UN","UF"))
ix<-Treatments=="CKR" | Treatments=="CKN" | Treatments=="CKF"
pca<-rda(otu,scale=T)
importance<-summary(pca)[["cont"]][["importance"]]
siteScore<-summary(pca)[["sites"]]
tempDf<-data.frame(x=siteScore[,1],
                   y=siteScore[,2],
                   Treatments=Treatments,
                   Label=1:54)

drawPCA<-function(tempDf,fileName){
  # Find the CONVEX polygons that surround each group
  hulls <- plyr::ddply(tempDf, "Treatments", function(df) df[chull(df$x, df$y), ])
  ggplot(tempDf, aes(x = x, y = y,color = Treatments,fill=Treatments))+
    geom_point(size=3)+
    # stat_ellipse(aes(x = x, y = y, color = Treatments,size = 2),show.legend=F)+
    geom_polygon(data = hulls, alpha = 0.5)+
    geom_text_repel(aes(label=Label),max.overlaps=Inf)+
    xlab(paste0("PC1(",round(importance[2,1]*100,2),"%)"))+
    ylab(paste0("PC2(",round(importance[2,2]*100,2),"%)"))+
    theme(text = element_text(size = 30))+
    ggsave(fileName,width = 10.24, height = 7.68,dpi=100)
}

drawPCA(tempDf[ix,],"CKR CKN CK rhizosphere effect PCA.png")

ix<-Treatments=="UR" | Treatments=="UN" | Treatments=="UF"
drawPCA(tempDf[ix,],"UR UN UF rhizosphere effect PCA.png")
```

## set font

```{r}
library(extrafont)
# copy fonts 
# cp times.ttf /usr/share/fonts/local/
# import fonts
#font_import()
# fonts()  
# loadfonts()
drawPCA<-function(tempDf,fileName){
  # Find the CONVEX polygons that surround each group
  hulls <- plyr::ddply(tempDf, "Treatments", function(df) df[chull(df$x, df$y), ])
  ggplot(tempDf, aes(x = x, y = y,color = Treatments,fill=Treatments))+
    geom_point(size=3)+
    # stat_ellipse(aes(x = x, y = y, color = Treatments,size = 2),show.legend=F)+
    geom_polygon(data = hulls, alpha = 0.5)+
    # geom_text_repel(aes(label=Label),max.overlaps=Inf,family="Times New Roman")+
    xlab(paste0("PC1(",round(importance[2,1]*100,2),"%)"))+
    ylab(paste0("PC2(",round(importance[2,2]*100,2),"%)"))+
    theme(text = element_text(size = 30,family="Times New Roman"))+
    ggsave(fileName,width = 10.24, height = 7.68,dpi=100)
}

ix<-Treatments=="CKR" | Treatments=="CKN" | Treatments=="CKF"
drawPCA(tempDf[ix,],"CKR CKN CK rhizosphere effect PCA2.png")

ix<-Treatments=="UR" | Treatments=="UN" | Treatments=="UF"
drawPCA(tempDf[ix,],"CKR CKN CK rhizosphere effect PCA2.png")
```