sommer (version 4.3.5)

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, PVCN=NULL, ylim=NULL, ...)

Value

If all parameters are correctly indicated the program will return:

$plot.data

a manhattan plot

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.

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.

Author

Giovanny Covarrubias-Pazaran

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

See Also

The core functions of the package mmer

Examples

#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)