manhattan: Creating a manhattan plot

Description

This function was designed to create a manhattan plot using a data frame with columns "Chrom" (Chromosome), "Position" and "p.val" (significance for the test).

Usage

manhattan(map, col=NULL, fdr.level=0.05, show.fdr=TRUE)

Arguments

map

the data frame with 3 columns with names; "Chrom" (Chromosome), "Position" and "p.val" (significance for the test).

col

colors prefered by the user to be used in the manhattan plot. The default is NULL which will use the red-blue palette.

fdr.level

false discovery rate to be drawn in the plot.

show.fdr

a TRUE/FALSE value indicating if the FDR value should be shown in the manhattan plot or not. By default is TRUE meaning that will be displayed.

Value

If all parameters are correctly indicated the program will return:

References

Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744

Examples

Run this code

#random population of 200 lines with 1000 markers
M <- matrix(rep(0,200*1000),1000,200)
for (i in 1:200) {
  M[,i] <- ifelse(runif(1000)<0.5,-1,1)
}
colnames(M) <- 1:200
set.seed(1234)
pp <- abs(rnorm(500,0,3));pp[23:34] <- abs(rnorm(12,0,20))
geno <- data.frame(Locus=paste("m",1:500, sep="."),Chrom=sort(rep(c(1:5),100)),
                   Position=rep(seq(1,100,1),5),
                   p.val=pp, check.names=FALSE)
geno$Locus <- as.character(geno$Locus)
## look at the data, 5LGs, 100 markers in each
## -log(p.val) value for simulated trait
head(geno)
tail(geno)
manhattan(geno)