Learn R Programming

qtl (version 1.70)

mqmplot.cistrans: cis-trans plot

Description

Plot results for a genomescan using a multiple-QTL model. With genetic location for the traits it is possible to show cis- and trans- locations, and detect trans-bands

Usage

mqmplot.cistrans(result, cross, threshold=5, onlyPEAK=TRUE,
                 highPEAK=FALSE, cisarea=10, pch=22, cex=0.5,
                 verbose=FALSE, ...)

Value

Plotting routine, so no return

Arguments

result

An object of class mqmmulti. See mqmscanall for details.

cross

An object of class cross. See read.cross for details.

threshold

Threshold value in LOD, Markers that have a LOD score above this threshold are plotted as small squares (see pch parameter). The markers with LODscores below this threshold are not visible

onlyPEAK

Plot only the peak markers ? (TRUE/FALSE) (Peak markers are markers that have a QTL likelihood above threshold and higher than other markers in the same region)

highPEAK

Highlight peak markers ? (TRUE/FALSE). When using this option peak markers (the marker with the highest LOD score in a region above the threshold gets an 25% increase in size and is displayed in red)

cisarea

Adjust the two green lines around the line y=x

pch

What kind of character is used in plotting of the figure (Default: 22, small square)

cex

Size of the points plotted (default to 0.5 half of the original size)

verbose

If TRUE, give verbose output

...

Extra parameters will be passed to points

Author

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

Run this code
data(multitrait)
multitrait <- subset(multitrait, chr=1,
                               ind=!apply(multitrait$pheno,
                                          1, function(a) any(is.na(a))))
data(locations)
multiloc <- addloctocross(multitrait,locations)
multiloc <- calc.genoprob(multiloc)
results <- scanall(multiloc, method="hk")
mqmplot.cistrans(results, multiloc, 5, FALSE, TRUE)

Run the code above in your browser using DataLab