The function `plot.trioGxE`

uses the calculations made in `trioGxE`

and
plots the point- and interval-estimates of gene-environment interaction
between a single nucleotide polymorphism (SNP) and a continuously varying environmental or non-genetic
covariate in case-parent trio data.

1 2 3 |

`x` |
A returned object produced by |

`se` |
A logical or a positive number.
When |

`seWithGxE.only` |
If |

`ylim` |
Either a list holding two length-2 numeric vectors that give different y-coordinate ranges for the two plots, or a single length-2 vector that gives equal y-coordinate ranges for both plots. |

`yscale` |
If |

`xlab` |
An optional string setting the title for the x-axis. |

`ylab` |
An optional string setting the title for the y-axis. |

`rugplot` |
Logical indicating whether to add rug representation of the data to the plots.
Default ( |

`...` |
Further graphical parameters passed to |

The function produces two plots in a 2 x 1 layout.
The first plot in the left panel displays the estimated gene-environment interaction (GxE) curve
related to *{\rm GRR}_1*, the genotype relative risks (GRRs) among the individuals with one copy
of the putative risk allele compared to those with zero copies.
The right panel displays the estimated GxE curve related to *{\rm GRR}_2*,
the GRRs among the individuals with two copies of the risk allele compared to those with one copy.

When `object$penmod="codominant"`

(with `se=TRUE`

),
confidence intervals are plotted for both interaction curves that are related to *{\rm GRR}_1* and *{\rm GRR}_2*.
When `object$penmod="dominant"`

, the confidence intervals are plotted only in the left panel,
but not in the right panel because *{\rm GRR}_2* is not estimated but set to be 1 under this penetrance mode.
Similarly, when `object$penmod="recessive"`

, the confidence intervals are plotted only in the right panel,
but not in the right panel because *{\rm GRR}_1* is not estimated but set to be 1 under this penetrance mode.
When `object$penmod="additive"`

, equivalent confidence intervals
are plotted in both panels, which display equivalent fitted curves.
This is because *{\rm GRR}_1* and *{\rm GRR}_2* are set to be equivalent
under the log-additive or multiplicative penetrance mode.

When `se`

is `TRUE`

or a positive number, standard error lines are plotted
based on the calculations of the Bayesian posterior variance estimates of the generalized
additive model parameters for GRRs (Wood, 2006).

Ji-Hyung Shin <shin@sfu.ca>, Brad McNeney <mcneney@sfu.ca>, Jinko Graham <jgraham@sfu.ca>

Shin, J.-H. (2012): *Inferring gene-environment interaction from case-parent trio data: evaluation of and adjustment for spurious G\times E and development of a data-smoothing method to uncover true G\times E*, Ph.D. thesis, Statistics and Actuarial Science, Simon Fraser University: URL https://theses.lib.sfu.ca/sites/all/files/public_copies/etd7214-j-shin-etd7214jshin.pdf.

Wood, S. (2006): *Generalized Additive Models: An Introduction with R*, Boca Raton, FL: Chapman & Hall/CRC.

`trioGxE`

, `test.trioGxE`

, `trioSim`

1 2 3 4 5 6 7 8 | ```
data(hypoTrioDat)
## fitting a co-dominant model to the hypothetical data
simfit <- trioGxE(data=hypoTrioDat,pgenos=c("parent1","parent2"),cgeno="child",cenv="attr",
k=c(5,5),knots=NULL,sp=NULL)
## produce the graphical display of the point- and interval-estimates of GxE curve
plot.trioGxE(simfit) # or just plot(simfit)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.