print.trioFS: Printing and plotting of a trioFS object
In trio: Testing of SNPs and SNP Interactions in Case-Parent Trio Studies

Description Usage Arguments Author(s) See Also Examples

Prints or plots the most important interactions found in a trioFS analysis.

## S3 method for class 'trioFS'
print(x, topX = 5, show.prop = TRUE, coded = FALSE, digits = 2, ...)

## S3 method for class 'trioFS'
plot(x, topX = 15, show.prop = FALSE, coded = TRUE, cex = 0.9, 
   pch = 16, col = 1, force.topX = FALSE, include0 = TRUE, add.v0 = TRUE, 
   v0.col = "grey50", main = NULL, ...)

`x`	an object of class `trioFS`, i.e. the output of `trioFS`.
`topX`	integer specifying how many interactions should be shown. If `topX` is larger than the number of interactions contained in `x`, all the interactions are shown. Additionally to the `topX` most important interactions, any interaction having the same importance as the `topX` most important one are `print`ed or (if `force.topX = FALSE`) `plot`ted.
`show.prop`	should the proportions of models containing the respective interactions be added to the output (if `print` is used)? If the output of `trioFS` should be `plot`ted, then the proportions of models can be plotted instead of the values of the importance measure by setting `show.prop = TRUE`.
`coded`	should the coded variable names be displayed? Might be useful if the actual variable names are pretty long. The coded variable name of the j-th variable is `Xj`.
`digits`	number of digits shown in the `print`ed output.
`cex`	a numeric value specifying the relative size of the text and symbols.
`pch`	specifies the used symbol. See the help of `par` for details.
`col`	the color of the text and the symbols. See the help of `par` for how colors can be specified.
`force.topX`	if `TRUE` exactly `topX` interactions are `plot`ted. If `FALSE` (default) all interactions up to the `topX`th most important one and all interactions having the same importance as the `topX`th most important one are `plot`ted.
`include0`	should the x-axis include zero regardless whether the importances of the shown interactions are much higher than 0?
`add.v0`	should a vertical line be drawn at x = 0? Ignored if `include0 = FALSE` and all importances are larger than zero.
`v0.col`	the color of the vertical line at x = 0. See the help page of `par` for how colors can be specified.
`main`	character string naming the title of the plot. If `NULL`, a standard title is added to the plot.
`...`	Ignored.

Holger Schwender, holger.schwender@udo.edu

trioFS

# Load the simulated data.
data(trio.data)

# Prepare the data in trio.ped1 for a trioFS analysis 
# by first calling
trio.tmp <- trio.check(dat = trio.ped1)

# and then applying
set.seed(123456)
trio.bin <- trio.prepare(trio.dat=trio.tmp, blocks=c(1,4,2,3))

# where we here assume the block structure to be
# c(1, 4, 2, 3), which means that the first LD "block"
# only consists of the first SNP, the second LD block
# consists of the following four SNPs in trio.bin,
# the third block of the following two SNPs,
# and the last block of the last three SNPs.
# set.seed() is specified to make the results reproducible.

# For the application of trioFS, some parameters of trio 
# logic regression are changed to make the following example faster.
my.control <- lrControl(start=1, end=-3, iter=1000, output=-4)

# Please note typically you should consider much more
# than 1000 iterations (usually, at least a few hundred
# thousand).

# TrioFS can then be applied to the trio data in trio.ped1 by
fs.out <- trioFS(trio.bin, control=my.control, rand=9876543)

# where we specify rand just to make the results reproducible.

# The output of trioFS can be printed by
fs.out

# By default, the five most important interactions are displayed.
# If another number of interactions, e.g., 10, should be shown,
# then this can be done by
print(fs.out, topX = 10)

# The importances can also be plotted by
plot(fs.out)