mqmautocofactors {qtl} | R Documentation |
Automatic setting of cofactors, taking marker density into account
Description
Sets cofactors, taking underlying marker density into account. Together
with mqmscan
cofactors are selected through backward elimination.
Usage
mqmautocofactors(cross, num=50, distance=5, dominance=FALSE, plot=FALSE, verbose=FALSE)
Arguments
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. |
Value
A list of cofactors to be used with mqmscan
.
Author(s)
Ritsert C Jansen; Danny Arends; Pjotr Prins; Karl W Broman broman@wisc.edu
See Also
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
Examples
data(hyper) # hyper dataset
hyperfilled <- fill.geno(hyper)
cofactors <- mqmautocofactors(hyperfilled,15) # Set 15 Cofactors
result <- mqmscan(hyperfilled,cofactors) # Backward model selection
mqmgetmodel(result)