R: Automatic setting of cofactors, taking marker density into...

mqmautocofactors {qtl} | R Documentation

## 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`.

### Author(s)

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

        data(hyper)                     # hyper dataset

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

[Package qtl version 1.46-2 Index]