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RDA.python2.py
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RDA.python2.py
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#!/usr/bin/python
# -*- coding: utf-8 -*-
import argparse
import re
import sys
import os
#*********************************************************************** *********************************************************************************
# argument:
p = argparse.ArgumentParser(
description="This script is used to plot RDA of species. The numeric enviroment factors must be encluded in maping file. The categories will be filterd before RDA")
p.add_argument('-i', '--input', dest='input', metavar='<path>',
help='Taxonomic count data file')
p.add_argument('-o', '--output', dest='output', metavar='<directory>', default='./',
help='Given an output directory')
p.add_argument('-m', '--metadata', dest='meta', metavar='<path>',
help='Sample metadata file')
p.add_argument('-g', '--group', dest='group', metavar='<str>',
help='Column name in sample-metadata file')
p.add_argument('-n', '--number', dest='number', metavar='<int>', default='20',
help='Specify how many species to be display, defaulf is 20')
p.add_argument('-e', '--exclude', dest='exclude', metavar='<str>', default='none',
help='Specify numeric variables excluded from rda seprated by commas,use "none" if all numeric variables is expected')
options = p.parse_args()
if not options.input and options.group and options.meta:
p.error("must have argument -i -m -g")
sys.exit()
else:
pass
if not os.path.exists(options.output):
os.makedirs(options.output)
rscript = open('rda.R', 'w')
print >>rscript, ('''
library(vegan)
library(stringr)
library(ggrepel)
library(ggplot2)
library(RColorBrewer)
ex<-str_split("%s",",")[[1]]
dat <- read.table("%s", header = TRUE, sep = "\\t",comment.char = "",check.names = F)
dat[,2:(ncol(dat)-1)]=apply(dat[,2:(ncol(dat)-1)],2,function(x){x/sum(x)})
dat<-dat[!duplicated(dat[,1]),]
rownames(dat)=dat[,1]
map<-read.table("%s",header = T,na.strings="",sep = "\\t",row.names=1,comment.char = "",check.names = F,stringsAsFactors = F)
notstr=c()
for(i in 1:length(map)){
notstr[i]=is.numeric(map[,i])
}
if(ex[1]!="none"){
notstr=notstr&(!colnames(map)%%in%%ex)
}
sel=c("%s",colnames(map)[notstr])
data=map[sel]
data=na.omit(data)
dat=dat[,-c(1,ncol(dat))]
dat=t(dat)[match(rownames(data),colnames(dat)),]
groups<-data[,1]
envdata<-data[sel[-1]]
dca <- decorana(veg = dat)
dcam <- max(dca$rproj)
if (dcam > 4){
cca <- cca(formula=dat~.,data=envdata, scale = TRUE, na.action = na.exclude)
pre <- "CCA"
}else{
cca <- rda(formula=dat~.,data=envdata,scale = TRUE, na.action = na.exclude)
pre <- "RDA"
}
path="%s"
ccascore <- scores(cca)
write.table(ccascore$sites, file = paste(path,"/","%s_", pre, ".sample.txt", sep = ""), sep = "\\t")
write.table(ccascore$species, file = paste(path,"/","%s_", pre, ".bacteria.txt", sep = ""), sep = "\\t")
envfit <- envfit(cca, envdata, permu = 2000, na.rm = TRUE)
rp <- cbind(as.matrix(envfit$vectors$r), as.matrix(envfit$vectors$pvals))
colnames(rp) <- c("r2", "Pr(>r)")
env <- cbind(envfit$vectors$arrows, rp)
write.table(as.data.frame(env), file = paste(path,"/", "%s_",pre, ".envfit.txt", sep = ""),sep = "\\t")
new<-cca$CCA
#samples=data.frame(ccascore$sites)
samples=data.frame(new$u)
samples$id=rownames(samples)
samples=data.frame(samples,%s=groups)
#species=data.frame(ccascore$species)
species=data.frame(new$v)
species$id=rownames(species)
species<-species[match(colnames(dat),rownames(species)),]
sum<-scale(colSums(dat))[,1]
species$abundance<-sum-min(sum)+0.8
number<-%s+1
if (dim(dat)[2]<number){
cut=-1
}else{
cut=sort(colSums(dat),T)[number]
}
show_species<-species[colSums(dat)>cut,]
hide_species<-species[colSums(dat)<=cut,]
print(paste("The threshold of abundance is:",cut))
#envis=data.frame(envfit$vectors$arrows)#Envis seem to be the same length after permutation
envis=data.frame(new$biplot)
envis$id=rownames(envis)
pc1 = cca$CCA$eig[1]/sum(cca$CCA$eig) * 100
pc2 = cca$CCA$eig[2]/sum(cca$CCA$eig) * 100
xlab <- paste(pre, "1: ", round(pc1, digits = 2), "%%", sep = "")
ylab <- paste(pre, "2: ", round(pc2, digits = 2), "%%", sep = "")
if(pre=="RDA"){
envis[,1]<-envis[,1]*0.5
envis[,2]<-envis[,2]*0.5
p1<-ggplot(data=samples,aes(x=RDA1,y=RDA2)) +
geom_point(aes(x=RDA1,y=RDA2,color=%s),size=3) +
#geom_text_repel(aes(x=RDA1,y=RDA2,label=id),color="black",size=3)+
geom_text_repel(data=envis,aes(x=RDA1,y=RDA2,label=id),color="black",size=5) +
geom_hline(yintercept=0,linetype="dotted") + geom_vline(xintercept=0,linetype="dotted")+
theme_bw() + theme(panel.grid=element_blank())+xlab(xlab)+ylab(ylab)+
labs(title=paste(pre," sample location plot",sep=""))+
geom_segment(aes(x=0,y=0,xend = RDA1, yend = RDA2),data = envis,
color=brewer.pal(8,"Accent")[6],size=1,
arrow = arrow(length = unit(0.2,"cm")))+
theme(title = element_text(size = 15,vjust = 0.5,hjust = 0.5),
axis.text = element_text(size = 15),
text = element_text(size = 15),
axis.title = element_text(size = 15),
legend.title = element_text(size = 15),
legend.text = element_text(size = 15))
ggsave(paste(path,"/","%s_",pre,"_sample_location_plot.png",sep=""),plot=p1,width = 8,height = 7,dpi = 300)
ggsave(paste(path,"/","%s_",pre,"_sample_location_plot.pdf",sep=""),plot=p1,width = 8,height = 7,dpi = 300)
envis[,1]<-envis[,1]*0.5
envis[,2]<-envis[,2]*0.5
p2<-ggplot(data=show_species,aes(x=RDA1,y=RDA2)) +
geom_point(aes(x=RDA1,y=RDA2,size=abundance),color=rainbow(3)[1]) +
geom_point(data=hide_species,aes(x=RDA1,y=RDA2,size=abundance),color="grey") +
guides(size=F)+
geom_text_repel(data=envis,aes(x=RDA1,y=RDA2,label=id),color="black",size=5) +
geom_text_repel(aes(RDA1,RDA2,label=id)) +
geom_hline(yintercept=0,linetype="dotted") + geom_vline(xintercept=0,linetype="dotted")+
theme_bw() + theme(panel.grid=element_blank())+xlab(xlab)+ylab(ylab)+
ggtitle(paste(pre," bacteria location plot",sep=""))+
geom_segment(aes(x=0,y=0,xend = RDA1, yend = RDA2),data = envis,
color=brewer.pal(8,"Accent")[6],size=1,
arrow = arrow(length = unit(0.2,"cm")))+
theme(title = element_text(size = 15,vjust = 0.5,hjust = 0.5),
axis.text = element_text(size = 15),
text = element_text(size = 15),
axis.title = element_text(size = 15),
legend.title = element_text(size = 15),
legend.text = element_text(size = 15))
ggsave(paste(path,"/","%s_",pre,"_bacteria_location_plot.png",sep=""),plot=p2,width = 7,height = 7,dpi = 300)
ggsave(paste(path,"/","%s_",pre,"_bacteria_location_plot.pdf",sep=""),plot=p2,width = 7,height = 7,dpi = 300)
}else{
envis[,1]<-envis[,1]*3.5
envis[,2]<-envis[,2]*3.5
p1<-ggplot(data=samples,aes(x=CCA1,y=CCA2)) +
geom_point(aes(x=CCA1,y=CCA2,color=%s),size=3) +
#geom_text_repel(aes(x=CCA1,y=CCA2,label=id),color="black",size=3)+
geom_text_repel(data=envis,aes(x=CCA1,y=CCA2,label=id),color="black",size=5) +
geom_hline(yintercept=0,linetype="dotted") + geom_vline(xintercept=0,linetype="dotted")+
theme_bw() + theme(panel.grid=element_blank())+xlab(xlab)+ylab(ylab)+
labs(title=paste(pre," sample location plot",sep=""))+
geom_segment(aes(x=0,y=0,xend = CCA1, yend = CCA2),data = envis,
color=brewer.pal(8,"Accent")[6],size=1,
arrow = arrow(length = unit(0.2,"cm")))+
theme(title = element_text(size = 15,vjust = 0.5,hjust = 0.5),
axis.text = element_text(size = 15),
text = element_text(size = 15),
axis.title = element_text(size = 15),
legend.title = element_text(size = 15),
legend.text = element_text(size = 15))
ggsave(paste(path,"/","%s_",pre,"_sample_location_plot.png",sep=""),plot=p1,width = 8,height = 7,dpi = 300)
ggsave(paste(path,"/","%s_",pre,"_sample_location_plot.pdf",sep=""),plot=p1,width = 8,height = 7,dpi = 300)
p2<-ggplot(data=show_species,aes(x=CCA1,y=CCA2)) +
geom_point(aes(x=CCA1,y=CCA2,size=abundance),color=rainbow(3)[1]) +
geom_point(data=hide_species,aes(x=CCA1,y=CCA2,size=abundance),color="grey") +
guides(size=F)+
geom_text_repel(data=envis,aes(x=CCA1,y=CCA2,label=id),color="black",size=5) +
geom_text_repel(aes(CCA1,CCA2,label=id)) +
geom_hline(yintercept=0,linetype="dotted") + geom_vline(xintercept=0,linetype="dotted")+
theme_bw() + theme(panel.grid=element_blank())+xlab(xlab)+ylab(ylab)+
ggtitle(paste(pre," bacteria location plot",sep=""))+
geom_segment(aes(x=0,y=0,xend = CCA1, yend = CCA2),data = envis,
color=brewer.pal(8,"Accent")[6],size=1,
arrow = arrow(length = unit(0.2,"cm")))+
theme(title = element_text(size = 15,vjust = 0.5,hjust = 0.5),
axis.text = element_text(size = 15),
text = element_text(size = 15),
axis.title = element_text(size = 15),
legend.title = element_text(size = 15),
legend.text = element_text(size = 15))
ggsave(paste(path,"/","%s_",pre,"_bacteria_location_plot.png",sep=""),plot=p2,width = 7,height = 7,dpi = 300)
ggsave(paste(path,"/","%s_",pre,"_bacteria_location_plot.pdf",sep=""),plot=p2,width = 7,height = 7,dpi = 300)
}
''' % (options.exclude, options.input, options.meta, options.group, options.output,
options.group, options.group, options.group, options.group, options.number,
options.group, options.group, options.group, options.group, options.group, options.group,
options.group, options.group, options.group, options.group))
rscript.close()
os.system('Rscript rda.R')
#os.remove('rda.R')