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

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 `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 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")

[Package qtl version 1.46-2 Index]