| mqmautocofactors | R Documentation |
Sets cofactors, taking underlying marker density into account. Together
with mqmscan cofactors are selected through backward elimination.
mqmautocofactors(cross, num=50, distance=5, dominance=FALSE, plot=FALSE, verbose=FALSE)
cross |
An object of class |
num |
Number of cofactors to set (warns when setting too many cofactors). |
distance |
Minimal distance between two cofactors, in cM. |
dominance |
If TRUE, create a cofactor list that is safe to use
with the dominance scan mode of MQM. See |
plot |
If TRUE, plots a genetic map displaying the selected markers as cofactors. |
verbose |
If TRUE, give verbose output. |
A list of cofactors to be used with mqmscan.
Ritsert C Jansen; Danny Arends; Pjotr Prins; Karl W Broman broman@wisc.edu
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(hyper) # hyper dataset
hyperfilled <- fill.geno(hyper)
cofactors <- mqmautocofactors(hyperfilled,15) # Set 15 Cofactors
result <- mqmscan(hyperfilled,cofactors) # Backward model selection
mqmgetmodel(result)
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