Learn R Programming

qtl (version 1.38-4)

mqmautocofactors: 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 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.

Value

  • A list of cofactors to be used with mqmscan.

See Also

    % \input{"inst/docs/Sources/MQM/mqm/standard_seealso.txt"}
  • 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 % -----^^ inst/docs/Sources/MQM/mqm/standard_seealso.txt ^^-----

Examples

Run this code
data(hyper)				        # hyper dataset
	hyper <- hyper[1:5]
	hyperfilled <- fill.geno(hyper)
	cofactors <- mqmautocofactors(hyperfilled,15)	# Set 15 Cofactors
	result <- mqmscan(hyperfilled,cofactors)	# Backward model selection
	mqmgetmodel(result)

Run the code above in your browser using DataLab