Heatmap of a genome of MQM scan on multiple phenotypes
Plotting routine to display a heatmap of results obtained from a multiple-QTL model on multiple phenotypes (the
output of 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"), ...)cross |
An object of class |
result |
Result object from mqmscanall, the object needs to be of class |
directed |
Take direction of QTLs into account (takes more time because of QTL direction calculations |
legend |
If TRUE, add a legend to the plot |
breaks |
Color break points for the LOD scores |
col |
Colors used between breaks |
... |
Additional arguments passed to the |
Danny Arends danny.arends@gmail.com
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
data(multitrait) multitrait <- fill.geno(multitrait) # impute missing genotype data result <- mqmscanall(multitrait, logtransform=TRUE) mqmplot.heatmap(multitrait,result)
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