mqmplot.multitrait {qtl} | R Documentation |
Plot the results from a genomescan using a multiple-QTL model on multiple phenotypes
Description
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
Usage
mqmplot.multitrait(result, type=c("lines","image","contour","3Dplot"),
group=NULL, meanprofile=c("none","mean","median"),
theta=30, phi=15, ...)
Arguments
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 |
Author(s)
Danny Arends danny.arends@gmail.com
See Also
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
Examples
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")