Description Usage Arguments Author(s) See Also Examples
Plotting routine to display a heatmap of results obtained from a multiple-QTL model on multiple phenotypes (the
output of mqmscanall
)
1 2 3 |
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: 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
1 2 3 4 5 | data(multitrait)
multitrait <- fill.geno(multitrait) # impute missing genotype data
result <- mqmscanall(multitrait, logtransform=TRUE)
mqmplot.heatmap(multitrait,result)
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