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).
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.
PVCN: In case the user wants to provide the name of the column that should be treated as the "p.val" column expected by the program in the 'map' argument.
ylim: the y axis limits for the manhattan plot if the user wants to customize it. By default the plot will reflect the minimum and maximum values found.
...: additional arguments to be passed to the plot function such as pch, cex, etc.
Returns
If all parameters are correctly indicated the program will return:
$plot.data: a manhattan plot
References
Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744
Author(s)
Giovanny Covarrubias-Pazaran
Examples
#random population of 200 lines with 1000 markersM <- matrix(rep(0,200*1000),1000,200)for(i in1:200){ M[,i]<- ifelse(runif(1000)<0.5,-1,1)}colnames(M)<-1:200set.seed(1234)pp <- abs(rnorm(500,0,3));pp[23:34]<- abs(rnorm(12,0,20))geno <- data.frame(Locus=paste("m",1:500, sep="."),Chrom=sort(rep(c(1:5),100)), Position=rep(seq(1,100,1),5), p.val=pp, check.names=FALSE)geno$Locus <- as.character(geno$Locus)## look at the data, 5LGs, 100 markers in each## -log(p.val) value for simulated traithead(geno)tail(geno)manhattan(geno)