qb.covar {qtlbim} | R Documentation

## Examine GxE effect of covariates on main genetic effects.

### Description

Compare main effects with GxE effects to address correlation of estimates.

### Usage

    qb.covar(qbObject, element = "add", covar = 1, adjust.covar, chr, ...)
    ## S3 method for class 'qb.covar':
    summary(object, percent = 5, digits = 3, ...)
    ## S3 method for class 'qb.covar':
    print(x, ...)
    ## S3 method for class 'qb.covar':
    plot(x, percent = 5, cex, include.zero = TRUE, ...)

### Arguments

`qbObject` | Object of class `qb`.
`object` | Object of class `qb.covar`.
`x` | Object of class `qb.covar`.
`element` | Main effect to examine ("add" or "dom").
`covar` | Index to covariates used in MCMC samples.
`adjust.covar` | Adjustments to covariates. Default is `NA`, which adjusts by covariate mean values. Values are assumed to be in order of fixed covariates.
`chr` | Subset of chromosomes as integer vector.
`percent` | Percentile (0 to 100) for summaries.
`digits` | Number of significant digits to print.
`cex` | Character expansion for plots (default decreases with MCMC sample size).
`include.zero` | Include zero values in plot when `TRUE`.
`...` | Arguments passed through to inherited routines.

### Details

The diagonal dark green line of points on plots by chromosome indicate adjustment for covariates that have not been centered. Main effects are generally less correlated with GxE when covariates are first centered to have mean zero.

### Value

Objects of class `qb.covar` have three columns: main effect, GxE effect and chromosome. Summary objects have eight columns, three for main effect and GxE (mean, lower and upper percentile), followed by correlation and p-value. Summaries are done by chromosome.

### Author(s)

Brian S. Yandell

### References

http://www.qtlbim.org

### See Also

`qb.mcmc`

### Examples

    temp <- qb.covar(qbExample)
    summary(temp)
    plot(temp)

[Package qtlbim version 1.6.5 Index]