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qtl (version 1.70)

mqmsetcofactors: Set cofactors at fixed intervals, to be used with MQM

Description

Set cofactors, at fixed marker intervals. Together with mqmscan cofactors are selected through backward elimination.

Usage

mqmsetcofactors(cross, each = NULL, cofactors=NULL, sexfactors=NULL, verbose=FALSE)

Value

An list of cofactors to be passed into mqmscan.

Arguments

cross

An object of class cross. See read.cross for details.

each

Every 'each' marker will be used as a cofactor, when each is used the cofactors and sexfactors parameter is ignored

cofactors

List of cofactors to be analysed in the QTL model. To set cofactors use mqmautocofactors or mqmsetcofactors; when each is set, this parameter is ignored

sexfactors

list of markers which should be treated as dominant cofactors (sexfactors), when each is set, this parameter is ignored

verbose

If TRUE, print tracing information.

Author

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

Run this code
    data(hyper)                                 # Hyper dataset
    hyper <- hyper[1:5]
    hyperfilled <- fill.geno(hyper)
  # Automatic cofactors every third marker
    cofactors <- mqmsetcofactors(hyperfilled,3)
    result <- mqmscan(hyperfilled,cofactors)	# Backward model selection
    mqmgetmodel(result)
  #Manual cofactors at markers 3,6,9,12,40 and 60
  cofactors <- mqmsetcofactors(hyperfilled,cofactors=c(3,6,9,12,40,60))
    result <- mqmscan(hyperfilled,cofactors)	# Backward model selection
    mqmgetmodel(result)

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