Description Usage Arguments Value Author(s) Examples

`scanonevar`

conducts a genome scan in an experimental
cross, accommodating covariate effects in residual variance and identifying
genetic effects on residual variance.

1 2 3 4 | ```
scanonevar(cross, mean.formula = phenotype ~ mean.QTL.add + mean.QTL.dom,
var.formula = ~var.QTL.add + var.QTL.dom, chrs = qtl::chrnames(cross
= cross), scan_types = c("mQTL", "vQTL", "mvQTL"),
glm_family = "gaussian", return.covar.effects = FALSE)
``` |

`cross` |
The |

`mean.formula` |
The formula to describe the mean of the phenotype. Keywords are mean.QTL.add and mean.QTL.dom for the additive and dominance components of the QTL effect on the mean. dglm model will be fit if mean.formula has only fixed effects. hglm model will be fit if mean.formula has one or more random effects. |

`var.formula` |
The formula to describe the residual variance of the phenotype. Keywords are var.QTL.add and var.QTL.dom for the additive and dominance components of the QTL effect on residual phenotype variance. var.formula must have only fixed effects. |

`chrs` |
chromosomes to scan |

`scan_types` |
a vector containing at least one of 'mQTL', 'vQTL', and 'mvQTL', or up to all three. |

`glm_family` |
a character vector indicating the GLM family – either 'gaussian' or 'poisson' |

`return.covar.effects` |
Should covariate effects estimated at each locus be returned? |

27599

Robert W. Corty [email protected]

1 2 3 | ```
set.seed(27599)
test.cross <- qtl::sim.cross(map = qtl::sim.map(len = rep(20, 5), n.mar = 5), n.ind = 50)
scanonevar(cross = test.cross)
``` |

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