mqmautocofactors: Automatic setting of cofactors, taking marker density into...
In byandell/qtl: Tools for analyzing QTL experiments

Description Usage Arguments Value Author(s) See Also Examples

Sets cofactors, taking underlying marker density into account. Together with mqmscan cofactors are selected through backward elimination.

1	mqmautocofactors(cross, num=50, distance=5, dominance=FALSE, plot=FALSE, verbose=FALSE)

`cross`	An object of class `cross`. See `read.cross` for details.
`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 `mqmscan` for details.
`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 kbroman@biostat.wisc.edu

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

	data(hyper)				        # hyper dataset
	
	hyperfilled <- fill.geno(hyper)
	cofactors <- mqmautocofactors(hyperfilled,15)	# Set 15 Cofactors
	result <- mqmscan(hyperfilled,cofactors)	# Backward model selection
	mqmgetmodel(result)