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plot_Admixture.R
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#Admixture结果可视化
###最佳K的可视化
ta1 = read.table("ld.QC.75_noinclude0-502502-geno02-maf03.ped.map.3.4.Q")
head(ta1)
barplot(t(as.matrix(ta1)),col = rainbow(3),
xlab = "Individual",
ylab = "Ancestry",
border = NA)
#Admixture结果可视化
###全部K值群体的可视化
#setwd("D:/桌面/毕业论文/22.09.26-牛-毕业/22.10.07-文章实验/22.10.26-群体结构/admixture")
###Admixture结果的可视化
##=========================================
# sort columns according to the cor
sort.admixture <- function(admix.data){
k <- length(admix.data)
n.ind <- nrow(admix.data[[1]])
name.ind <- rownames(admix.data[[1]])
admix.sorted <- list()
if (admix.data[[1]][1,1] > admix.data[[1]][1,2]){
admix.sorted[[1]] <- admix.data[[1]]
}else{
admix.sorted[[1]] <- admix.data[[1]][,c(2,1)]
}
for (i in 1:(k-1)){
admix <- matrix(nrow = n.ind, ncol = (i + 2))
cors <- cor(admix.sorted[[i]], admix.data[[i + 1]])
sorted.loc <- c()
for (j in 1:nrow(cors)){
cor <- cors[j,]
cor[sorted.loc] <- NA
sorted.loc <- c(sorted.loc, which.max(cor))
}
sorted.loc <- c(sorted.loc, which(! 1:ncol(cors) %in% sorted.loc))
cat("n_max = ", sorted.loc, "\n")
admix <- admix.data[[i + 1]][,sorted.loc]
rownames(admix) <- name.ind
admix.sorted[[i + 1]] <- admix
}
return(admix.sorted)
}
sort.iid <- function(k.values, groups){
max.col <- which.max(colSums(k.values))
k.values <- cbind(k.values, groups[match(rownames(k.values), as.character(groups$iid)),])
k.values <- transform(k.values, group = as.factor(k.values$fid))
k.means <- tapply(k.values[,max.col], k.values$group, mean)
k.means <- k.means[order(k.means)]
k.sort <- data.frame(id = names(k.means), order = order(k.means),mean = k.means)
k.values$order <- k.sort[match(as.character(k.values$group), k.sort$id), 3]
k.values <- k.values[order(k.values$order, k.values[,max.col]),]
return(rownames(k.values))
}
sort.fid <- function(iid.order, fid.order, fam.table){
new.order <- c()
for (fid in fid.order){
new.order <- c(new.order, which(iid.order %in% fam.table[fam.table$fid == fid, "iid"]))
}
return(iid.order[new.order])
}
read.structure <- function(file, type = "structure"){
if (type == "structure"){
k.values <- read.table(file = file, header = F)
rownames(k.values) <- k.values[,1]
k.values[,1:3] <- NULL
}else{
k.values <- read.table(file = file, header = F)
}
return(k.values)
}
add.black.line <- function(data, groups, nline = 1){
data <- as.matrix(data)
group.name <- unique(groups)
new.data <- matrix(NA, ncol = ncol(data))
black.data <- matrix(NA, nrow = nline, ncol = ncol(data))
new.name <- c(NA)
for (name in group.name){
new.data <- rbind(new.data, black.data)
new.data <- rbind(new.data, data[which(groups == name),])
new.name <- c(new.name, rep(NA,nline))
new.name <- c(new.name, rownames(data)[which(groups == name)])
}
added.data <- new.data[(nline + 2):nrow(new.data),]
rownames(added.data) <- new.name[(nline + 2):nrow(new.data)]
return(added.data)
}
##=========================================
header <- "QC.67_admix-geno005-maf003-ld502502"
max.k <- 12
##=========================================
admix.fn <- paste(header, 2:max.k, "Q", sep = ".")
fam.fn <- paste(header, "fam", sep = ".")
admix.fam <- read.table(fam.fn, stringsAsFactors = F,col.names = c("fid", "iid", "pid", "mid", "sex", "pheno"))
admix.values <- lapply(admix.fn, read.table, header = F, row.names = as.character(admix.fam$iid))
order.fn <- paste(header, "order.txt", sep = ".")
admix.order <- read.table(order.fn, stringsAsFactors = F,col.names = c("region", "iid", "fid"))
id.order <- admix.order$iid
admix.data <- list()
for (i in 1:length(admix.values)){
admix.data[[i]] <- admix.values[[i]][id.order,]
}
species <- as.character(admix.order[,1])
sorted.data <- sort.admixture(admix.data)
## add black line in plot
nline <- 0
plot.data <- list()
group.order <- admix.order[match(id.order, admix.order$iid),3]
for (i in 1:length(sorted.data)){
plot.data[[i]] <- add.black.line(sorted.data[[i]], group.order, nline = nline)
}
## add xlab to plot
plot.id.list <- rownames(plot.data[[1]])
plot.xlab <- admix.order[match(x = plot.id.list, table = admix.order$iid),]
plot.lab <- unique(plot.xlab$fid)
plot.lab <- plot.lab[!is.na(plot.lab)]
plot.at <- c()
start <- 0
for (fid in plot.lab){
xlen <- length(which(plot.xlab$fid == fid))
gap <- start + floor(xlen / 2)
plot.at <- c(plot.at, gap)
start <- start + nline + xlen
}
##=========================================
## barplot admixture and structure
library(RColorBrewer)
my.colours <- c("#873186", "#6BB93F","#E20593", "#18A2CA","#FFB6C1","#DBB71D", "#F37020","#3364BC",
brewer.pal(8,"Dark2"),"#0b09c3","#f2640a","#08b052","#c00505","#0bc5ee","#7030a2","#ffff01","#c55911")
#brewer.pal(8, "Dark2")
# "#873186", "#E20593", "#6BB93F", "#18A2CA"
# "#3364BC", "#000000", "#F37020", "#DBB71D"
max.k <- length(plot.data)
n <- dim(plot.data[[1]])[1]
png(file=paste(header,"admix.plot.png",sep="."),res=400, width=2000, height=1200)
par(mfrow = c(max.k, 1),mar=c(0.1,0.7,0,0),oma=c(3.5,0,0.1,0.1), mgp=c(0,0.2,0),xaxs="i",cex.lab=0.6,font.lab=2,cex.axis=0.8)
par(las=2)
# define black line locate in where
plot.at1 <- c()
start <- 0
for (fid in plot.lab){
xlen <- length(which(plot.xlab$fid==fid))
gap <- start + floor(xlen)
plot.at1 <- c(plot.at1, gap)
start <- start+nline+xlen
}
# plot k
for (i in 1:max.k){
barplot(t(as.matrix(plot.data[[i]])),names.arg=rep(c(""),n),col=my.colours,border=NA,space=0,axes=F,ylab=paste("K=",i+1),xaxt="n",yaxt="n",font=2)
# plot black line for each pop in top bottom left and right
for (i in 0:(length(plot.at1))) {
x <- plot.at1[i]
abline(v=0, lwd=1, col="black")
abline(v=x, lwd=0.7, col="black")
}
abline(h=0, lwd=0.9, col="black")
# add top and bottom border for each subplot
rect(par("usr")[1], par("usr")[4] - i * nline / max.k ,
par("usr")[2], par("usr")[4] - (i-1) * nline / max.k , lwd = 1 )
}
axis(side=1,at=plot.at,labels=plot.lab,tick=F,font=2,cex.axis=0.6)
dev.off()
axis(side = 1, at = plot.at, labels = plot.lab, tick = F, font=2, cex.axis = 0.6)
dev.off()