#########################################
###### Author:Katharine Lee #############
############## 2017.07 ##################
#########################################
metaca <- function(
input,
output,
output_sp = NULL,
output_spt = NULL,
outputFormat = "png",
center = F,
scale = F,
main = NULL,
group = NULL,
group_colour = NULL,
select = NULL,
point_size = 8,
point_alpha = 1,
point_text_size = 4,
sp_colour = "royalblue4",
sp_size = 4,
width = 9,
height = 8
){
# library(ggplot2)
# library(vegan)
# library(xlsx)
# library(readxl)
# input = "/Bio/User/liyewei/total_otu_table_L3.txt"
t = read.table(input,header = T, skip = 1,sep = "\t",comment.char = "@",check.names = F)
if(length(unique(t[,1]))!=length(t[,1])){
id = which(sapply(1:ncol(t),function(i) is.numeric(t[,i])))
colnames(t)[1] = "otuid"
t[,1] = as.character(t[,1])
expr = paste0(colnames(t[,id]),"=sum(",colnames(t[,id]),")",collapse = ",")
expr = paste0("dplyr::summarise(group_by(t,otuid),",expr,")")
t = as.data.frame(eval(parse(text = expr)))
}
in_table <- as.data.frame(t[,2:(dim(t)[2])])
rownames(in_table) <- t[,1]
# colSums(in_table)
in_table2 <- data.frame(in_table,rowSums(in_table))
colnames(in_table2) = c(rownames(in_table2),"rowSums.in_table.")
in_table_order_by_row_sum <- in_table2[order(-in_table2$rowSums.in_table.),]
in_table = in_table_order_by_row_sum[,1:(dim(in_table_order_by_row_sum)[2]-1)]
if(!is.null(select)){
if(select >= dim(in_table)[1]){
in_table = in_table
}else{
in_table = in_table[1:as.numeric(select),]
}
}
## --------------------- CA analysis ---------------------- ##
ca <- cca(t(in_table),center=center,scale = scale)
# summary
sum_ca <- summary(ca)
(eigv_table <- sum_ca$cont$importance)
sp_df <- data.frame(sum_ca$species)
sites_df <- data.frame(sum_ca$sites)
# Eigenvalue
(eigv_ca_1 <- as.numeric(sprintf("%.3f",eigv_table[2,1]))*100)
(eigv_ca_2 <- as.numeric(sprintf("%.3f",eigv_table[2,2]))*100)
name <- row.names(sites_df)
sites_df$SitesID = name
# sites_df$Groups = groups
name <- row.names(sp_df)
sp_df$SpID = name
if(!is.null(group)) {groups <- unlist(strsplit(group,","))} else groups = group
sites_df$Groups = groups
# spname <- row.names(sp_df)
# sp_df$name = spname
# draw pca plot figure
xlab=paste("CA1(",eigv_ca_1,"%)",sep="")
ylab=paste("CA2(",eigv_ca_2,"%)",sep="")
# CA
ggca <- ggplot(sites_df,aes(CA1,CA2))
ggca = ggca +
xlab(xlab)
ggca = ggca +
ylab(ylab)
if(!is.null(main)) ggca <- ggca + labs(title = main)
ggca <- ggca +
geom_hline(yintercept=0,linetype=2,color="grey",size=.5) +
geom_vline(xintercept=0,linetype=2,color="grey",size=.5)
if(!is.null(group)){
ggca <- ggca +
geom_point(data = sites_df,size=point_size,alpha = point_alpha,aes(color=Groups))
}else{
ggca <- ggca +
geom_point(data = sites_df,size=point_size,alpha = point_alpha)
}
ggca = ggca + geom_text(data = sites_df,
size = point_text_size,
aes(label = SitesID),
color = "grey56")
# nudge_x = .02,
# nudge_y = .02)
# if(input$sites){
# ggca <- ggca +
# geom_text(data = sites_df, aes(label=SitesID, color=Groups),
# family="Times", size = point_size,
# nudge_x=.3,nudge_y=.1)
# }else{
# ggca <- ggca
# }
#
colours <- c("#F4BD6D","#87CCC5","olivedrab3","brown2","goldenrod1","deepskyblue3","maroon2","mediumpurple4",
"cadetblue4","darkblue","hotpink3","indianred1","gray59",
"darkorange1","slategray3","grey95","mediumorchid3","paleturquoise1",
"orangered4","grey64","gray62","royalblue4","antiquewhite3")
cols <- colours[1:dim(as.data.frame(table(sites_df$Groups)))[1]]
ggca <- ggca +
scale_colour_manual(values = cols)
if(!is.null(group_colour)) {col <- unlist(strsplit(group_colour,",")); ggca = ggca + scale_colour_manual(values = col)}
ggca <- ggca + theme_bw()
ggca <- ggca +
theme(legend.title = element_text(angle = 0,
hjust =.95,
vjust =.95,
size = 12),
legend.position = "right",
legend.background = element_rect(
colour = "white",
fill = "white",
size = 1,
linetype = 1),#'dashed'
legend.key.size = unit(.5, "cm"),
legend.key.height = unit(.5, "cm"),
legend.key.width = unit(.5, "cm"),
legend.text = element_text(angle = 0,
hjust =.95,
vjust =.95,
size = 10),
legend.justification = "top",
panel.background = element_rect(fill = "white",colour = "white",size = 1.5))
##########################################################################
ggcasp <- ggca +
geom_point(data = sp_df,
color ="royalblue4",
shape = 0,
alpha = .6,
size = 4)
ggcaspt <- ggca +
geom_text(data = sp_df,
aes(label = SpID),
color = sp_colour,
alpha = .7,
size = sp_size)
##########################################################################
Format = strsplit(outputFormat,",")[[1]]
sapply(Format,function(x){
if(x == "pdf") temp = paste0("cairo_pdf(file = paste0(output,\'.\',x), bg = \'transparent\', width = width, height = height)")
else temp = paste0(x,"(file = paste0(output,\'.\',x), bg = \'transparent\', width = width*72, height = height*72, type = \'cairo\')")
eval(parse(text = temp))
# png(file = paste0(output_hc,".",x), bg = "transparent", width = width, height = height)
plot(ggca)
dev.off()
if(!is.null(output_sp)){
if(x == "pdf") temp = paste0("cairo_pdf(file = paste0(output_sp,\'.\',x), bg = \'transparent\', width = width, height = height)")
else temp = paste0(x,"(file = paste0(output_sp,\'.\',x), bg = \'transparent\', width = width*72, height = height*72, type = \'cairo\')")
eval(parse(text = temp))
# png(file = paste0(output_hc,".",x), bg = "transparent", width = width, height = height)
plot(ggcasp)
dev.off()
}
if(!is.null(output_spt)){
if(x == "pdf") temp = paste0("cairo_pdf(file = paste0(output_spt,\'.\',x), bg = \'transparent\', width = width, height = height)")
else temp = paste0(x,"(file = paste0(output_spt,\'.\',x), bg = \'transparent\', width = width*72, height = height*72, type = \'cairo\')")
eval(parse(text = temp))
# png(file = paste0(output_hc,".",x), bg = "transparent", width = width, height = height)
plot(ggcaspt)
dev.off()
}
})
return(ggca)
# if(!is.null(output)) ggsave(output,
# ggca,
# width = 9,
# height = 8)
#
# if(!is.null(output_sp)) ggsave(output_sp,
# ggcasp,
# width = 9,
# height = 8)
#
# if(!is.null(output_spt)) ggsave(output_spt,
# ggcaspt,
# width = 9,
# height = 8)
}
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