| 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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