mqmplotmultitrait: Plot the results from a genomescan using a multiple-QTL model...

In qtl: Tools for Analyzing QTL Experiments

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 mqmscanall
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 plot.

Author(s)

Danny Arends [e-mail]

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")

qtl documentation built on Nov. 28, 2023, 1:09 a.m.