qtl (version 1.38-4)

mqmplot.multitrait: 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.

See Also

% \input{"inst/docs/Sources/MQM/mqm/standard_seealso.txt"}
• The MQM tutorial:http://www.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 % -----^^ inst/docs/Sources/MQM/mqm/standard_seealso.txt ^^-----

Examples

data(multitrait)
multitrait <- subset(multitrait, chr=1:2, ind=!apply(multitrait$pheno, 1, function(a) any(is.na(a))))
multitrait$pheno <- multitrait$pheno[,1:3]
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")