xpos_scan1(map, chr = NULL, gap = NULL, thechr, thepos)

# read data
iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2"))

# insert pseudomarkers into map
map <- insert_pseudomarkers(iron$gmap, step=1)

# calculate genotype probabilities
probs <- calc_genoprob(iron, map, error_prob=0.002)

# grab phenotypes and covariates; ensure that covariates have names attribute
pheno <- iron$pheno
covar <- match(iron$covar$sex, c("f", "m")) # make numeric
names(covar) <- rownames(iron$covar)
Xcovar <- get_x_covar(iron)

# perform genome scan
out <- scan1(probs, pheno, addcovar=covar, Xcovar=Xcovar)

# plot the results for selected chromosomes
ylim <- c(0, maxlod(out)*1.02) # need to strip class to get overall max LOD
chr <- c(2,7,8,9,15,16)
plot(out, map, chr=chr, ylim=ylim)
plot(out, map, lodcolumn=2, chr=chr, col="violetred", add=TRUE)
legend("topleft", lwd=2, col=c("darkslateblue", "violetred"), colnames(out),
       bg="gray90")

# Use xpos_scan1 to add points at the peaks
# first find the peaks with LOD > 3
peaks <- find_peaks(out, map)

# keep just the peaks for chromosomes that were plotted
peaks <- peaks[peaks$chr %in% chr,]

# find x-axis positions
xpos <- xpos_scan1(map, chr=chr, thechr=peaks$chr, thepos=peaks$pos)

# point colors
ptcolor <- c("darkslateblue", "violetred")[match(peaks$lodcolumn, c("liver", "spleen"))]

# plot points
points(xpos, peaks$lod, pch=21, bg=ptcolor)