simulateMissingData: Simulates missing genotype data

In kbroman/qtl: Tools for Analyzing QTL Experiments

Simulates missing genotype data

Description

Simulate missing genotype data by removing some genotype data from the cross object

Usage

  simulatemissingdata(cross, percentage = 5)

Arguments

cross	An object of class cross. See read.cross for details.
percentage	How much of the genotype data do we need to randomly drop?

Value

An object of class cross with percentage

Author(s)

Danny Arends [e-mail]

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(multitrait)
multitrait <- fill.geno(multitrait)
multimissing5 <- simulatemissingdata(multitrait,perc=5)
perc <- (sum(nmissing(multimissing5))/sum(ntyped(multimissing5)))

kbroman/qtl documentation built on Jan. 13, 2024, 10:14 p.m.