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Plotting routine to display a heatmap of results obtained from a multiple-QTL model on multiple phenotypes (the output of mqmscanall)
mqmscanall
mqmplot.heatmap(cross, result, directed=TRUE, legend=FALSE, breaks = c(-100,-10,-3,0,3,10,100), col = c("darkblue","blue","lightblue","yellow","orange","red"), …)
An object of class cross. See read.cross for details.
cross
read.cross
Result object from mqmscanall, the object needs to be of class mqmmulti
mqmmulti
Take direction of QTLs into account (takes more time because of QTL direction calculations
If TRUE, add a legend to the plot
Color break points for the LOD scores
Colors used between breaks
Additional arguments passed to the image function
image
The MQM tutorial: http://www.rqtl.org/tutorials/MQM-tour.pdf
MQM - MQM description and references
MQM
mqmscan - Main MQM single trait analysis
mqmscan
mqmscanall - Parallellized traits analysis
mqmaugment - Augmentation routine for estimating missing data
mqmaugment
mqmautocofactors - Set cofactors using marker density
mqmautocofactors
mqmsetcofactors - Set cofactors at fixed locations
mqmsetcofactors
mqmpermutation - Estimate significance levels
mqmpermutation
scanone - Single QTL scanning
scanone
data(multitrait) multitrait <- fill.geno(multitrait) # impute missing genotype data result <- mqmscanall(multitrait, logtransform=TRUE) mqmplot.heatmap(multitrait,result)
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