Plot the LOD curves for each partition for a genome scan with a single
diallelic QTL (the
output of scanPhyloQTL
).
# S3 method for scanPhyloQTL
plot(x, chr, incl.markers=TRUE,
col, xlim, ylim, lwd=2, gap=25, mtick=c("line", "triangle"),
show.marker.names=FALSE, alternate.chrid=FALSE, legend=TRUE, ...)
None.
An object of class "scanPhyloQTL"
, as output by
scanPhyloQTL
.
Optional vector indicating the chromosomes to plot.
This should be a vector of character strings referring to chromosomes
by name; numeric values are converted to strings. Refer to
chromosomes with a preceding -
to have all chromosomes but
those considered. A logical (TRUE/FALSE) vector may also be used.
Indicate whether to plot line segments at the marker locations.
Optional vector of colors to use for each partition.
Limits for x-axis (optional).
Limits for y-axis (optional).
Line width.
Gap separating chromosomes (in cM).
Tick mark type for markers (line segments or upward-pointing triangels).
If TRUE, show the marker names along the x axis.
If TRUE and more than one chromosome is plotted, alternate the placement of chromosome axis labels, so that they may be more easily distinguished.
Indicates whether to include a legend in the plot.
Passed to the function plot.scanone
when it
is called.
Karl W Broman, broman@wisc.edu
Broman, K. W., Kim, S., An\'e, C. and Payseur, B. A. Mapping quantitative trait loci to a phylogenetic tree. In preparation.
if (FALSE) {
# example map; drop X chromosome
data(map10)
map10 <- map10[1:19]
# simulate data
x <- simPhyloQTL(4, partition="AB|CD", crosses=c("AB", "AC", "AD"),
map=map10, n.ind=150,
model=c(1, 50, 0.5, 0))
# run calc.genoprob on each cross
x <- lapply(x, calc.genoprob, step=2)
# scan genome, at each position trying all possible partitions
out <- scanPhyloQTL(x, method="hk")
# maximum peak
max(out, format="lod")
# approximate posterior probabilities at peak
max(out, format="postprob")
# all peaks above a threshold for LOD(best) - LOD(2nd best)
summary(out, threshold=1, format="lod")
# all peaks above a threshold for LOD(best), showing approx post'r prob
summary(out, format="postprob", threshold=3)
# plot of results
plot(out)
}
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