sommer (version 1.3)

map.plot2: Creating a genetic map

Description

This function was designed to create a genetic map using a data frame indicating the Linkage Group (LG), Position and marker names (Locus).

Usage

map.plot2(data, trait = NULL, trait.scale = "same", 
        col.chr = NULL, col.trait = NULL, type = "hist", cex = 0.4,
        lwd = 1, cex.axis = 0.4, cex.trait=0.8, jump = 5)

Arguments

data

the data frame with 3 columns with names; Locus, LG and Position

trait

if something wants to be plotted next the linkage groups the user must indicate the name of the column containing the values to be ploted, i.e. p-values, LOD scores, X2 segregation distortion values, etc.

trait.scale

a character value indicating if the scale should be the same or different for each linkage group. The default value id "same".

col.chr

a vector with color names for the chromosomes

col.trait

a vector with color names for the trait plotted next to the LG's

type

a character value indicating if the trait should be plotted as scatterplot `dot`, histogram `hist`, line `line` next to the chromosomes.

cex

the cex value determining the value of the position number in the LGs

lwd

the width of the lines in the plot

cex.axis

the cex value for sizing the labels of LGs and traits plotted

cex.trait

the cex value for sizing the dots or lines of the trait plotted

jump

a scalar value indicating how often should be drawn a number next to the LG indicating the position. The default is 5 which means every 5 cM a label will be drawn, i.e. 0,5,10,15,... cM.

Value

• If all parameters are correctly indicated the program will return: [object Object]

References

Kang et al. 2008. Efficient control of population structure in model organism association mapping. Genetics 178:1709-1723.

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)
geno <- data.frame(Locus=1:500,LG=sort(rep(c(1:5),100)),
                   Position=rep(seq(1,100,1),5),
                   X2=rnorm(500,10,4), check.names=FALSE)
## look at the data, 5LGs, 100 markers in each
## X2 value for segregation distortion available
head(geno)
tail(geno)
map.plot2(geno, trait="X2", type="line")
map.plot2(geno, trait="X2", type="hist")
map.plot2(geno, trait="X2", type="dot")