R: Simulates missing genotype data

simulatemissingdata {qtl} | R Documentation

## 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 danny.arends@gmail.com

### See Also

- 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

### Examples

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

[Package qtl version 1.41-6 Index]