QTLRel (version 1.14)

plotit: Plotting

Description

Plot mapping results.

Usage

# S3 method for scanOne
plot(x,...)
plotit(lrt, cv, bychr = FALSE, chr.labels = TRUE, type = "p", lty = NULL,
   col = NULL, pch = NULL, cex = NULL, ...)

Arguments

x

Object from scanOne or scanTwo.

lrt

A data frame with (chr, dist, y,...) or (chr, dist, y, group,...), where "chr" represents chromosome, "dist" position on the chromosome, "y" the test statistic.

cv

Threshold to be drawn on the plot.

cex

See par.

bychr

A logical variable. If true, the plot will be displayed per chromosomes.

chr.labels

A logical variable. If true, the chromosome names will be drawn.

type,lty,col,pch

See plot.default.

...

Other options passed to R plot function. To call plot to plot results of scanOne, one may need to provide a genetic map gmap that should be data frame (snp, chr, dist, ...), where "snp" is the SNP (marker) name, "chr" is the chromosome where the "snp" is, and "dist" is the genetic distance in centi-Morgan (cM) from the left of the chromosome.

Examples

data(miscEx)

if (FALSE) {
# impute missing genotypes
pheno<- pdatF8[!is.na(pdatF8$bwt) & !is.na(pdatF8$sex),]
ii<- match(rownames(pheno), rownames(gdatF8))
geno<- gdatF8[ii,]
ii<- match(rownames(pheno), rownames(gmF8$AA))
v<- list(A=gmF8$AA[ii,ii], D=gmF8$DD[ii,ii])

gdat.imp<- genoImpute(geno, gmap=gmapF8, step=Inf,
   gr=8, na.str=NA)
# estimate variance components
o<- estVC(y=pheno$bwt, x=pheno$sex, v=v)

# genome scan
llk<- scanOne(y=pheno$bwt, x=pheno$sex, vc=o, gdat=gdat.imp)

# plotting
plot(llk, gmap=gmapF8) # gmap is needed

# plotting in another way
idx<- match(colnames(gdat.imp), gmapF8$snp)
tmp<- data.frame(chr=gmapF8$chr[idx],dist=gmapF8$dist[idx],y=llk$LRT)
plotit(tmp, main="Mapping Plot", xlab="Chromosome", ylab="LRT",
   col=as.integer(tmp$ch)%%2+2,type="p")
}