Plot the results from a genomescan using a multiple-QTL model on multiple phenotypes
Plotting routine to display the results from a multiple-QTL model on
multiple phenotypes. It supports four different visualizations: a
contourmap, heatmap, 3D graph or a multiple QTL plot created by using
plot.scanone on the mqmmulti object
mqmplot.multitrait(result, type=c("lines","image","contour","3Dplot"),
group=NULL, meanprofile=c("none","mean","median"),
theta=30, phi=15, ...)result |
Result object from |
type |
Selection of the plot method to visualize the data: "lines" (defaut plotting option), "image", "contour" and "3Dplot" |
group |
A numeric vector indicating which traits to plot. NULL means no grouping |
meanprofile |
Plot a mean/median profile from the group selected |
theta |
Horizontal axis rotation in a 3D plot |
phi |
Vertical axis rotation in a 3D plot |
... |
Additional arguments passed to |
Danny Arends danny.arends@gmail.com
The MQM tutorial: https://rqtl.org/tutorials/MQM-tour.pdf
MQM - MQM description and references
mqmscan - Main MQM single trait analysis
mqmscanall - Parallellized traits analysis
mqmaugment - Augmentation routine for estimating missing data
mqmautocofactors - Set cofactors using marker density
mqmsetcofactors - Set cofactors at fixed locations
mqmpermutation - Estimate significance levels
scanone - Single QTL scanning
data(multitrait) multitrait <- fill.geno(multitrait) # impute missing genotype data result <- mqmscanall(multitrait, logtransform=TRUE) mqmplot.multitrait(result,"lines") mqmplot.multitrait(result,"contour") mqmplot.multitrait(result,"image") mqmplot.multitrait(result,"3Dplot")
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