Nothing
qtl.heatmap = function(lod, ...) {
old.par = par(no.readonly = TRUE)
# Strip off the location data.
hdr = lod[,1:3]
lod = as.matrix(lod[,-1:-3])
# Get the chr boundaries and midpoints.
chrbnd = table(hdr$Chr)
chrbnd = chrbnd[order(as.numeric(names(chrbnd)))]
chrbnd = cumsum(chrbnd)
chrmid = c(0, chrbnd[-length(chrbnd)]) + diff(c(0, chrbnd)) * 0.5
# Exponentiate the data and then scale each phenotype between 0 and 1.
lod = exp(lod)
lod = lod / matrix(apply(lod, 2, max, na.rm = TRUE), nrow(lod), ncol(lod),
byrow = TRUE)
# Cluster the LOD profiles.
lod.cor = cor(lod, use = "pair")
lod.cl = hclust(as.dist(1.0 - lod.cor), method = "average")
lod = lod[,lod.cl$order]
dend = as.dendrogram(lod.cl)
# Create the heatmap.
layout(matrix(1:2, 1, 2), widths = c(0.1, 0.9))
par(plt = c(0.0, 1, 0.1, 0.9))
plot(dend, horiz = TRUE, axes = FALSE, yaxs = "i", leaflab = "none")
par(las = 1, plt = c(0, 0.8, 0.1, 0.9))
breaks = 0:100 / 100
col = colorRampPalette(c(gray(10:2/10), rgb(1,0.5,0), rgb(1,0,0)))(length(breaks) - 1)
image(1:nrow(lod), 1:ncol(lod), lod, breaks = breaks, col = col, ann = FALSE,
axes = FALSE, ...)
abline(h = 0:ncol(lod) + 0.5, col = "grey30")
abline(v = c(0, chrbnd), col = "grey30")
mtext(text = colnames(lod), side = 4, at = 1:ncol(lod))
mtext(names(chrbnd), side = 1, line = 0, at = chrmid, font = 2)
mtext(names(chrbnd), side = 3, line = 0, at = chrmid, font = 2)
# Legend along bottom.
width = nrow(lod) / length(col)
pin = par("pin")
usr = par("usr")
mai = par("mai")
usr.per.in = (usr[4] - usr[3]) / pin[2]
top = -mai[1] * 0.25 * usr.per.in
bottom = top - usr.per.in * 0.25
par(xpd = NA)
for(i in 1:length(col)) {
rect((i-1) * width, bottom, i * width, top, col = col[i], border = NA)
} # for(i)
par(old.par)
} # qtl.heatmap()
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