cpg.perm.object: Methods for object of class '"cpg.perm"'.
In CpGassoc: Association Between Methylation and a Phenotype of Interest

Description Usage Arguments Note Author(s) See Also Examples

Methods and extra functions for class "cpg.perm". plot.cpg.perm creates a QQ plot based on the association p-values or t-statistics from the function cpg.perm.

  ## S3 method for class 'cpg.perm'
plot(x, save.plot = NULL, file.type = "pdf", popup.pdf = FALSE,
  main.title = NULL, eps.size = c(5, 5), tplot = FALSE, perm.ci = TRUE, classic = TRUE,
  gc.p.val = FALSE, gcdisplay = FALSE, ...)

  ## S3 method for class 'cpg.perm'
summary(object,...)

  ## S3 method for class 'cpg.perm'
print(x,...)

  ## S3 method for class 'cpg.perm'
sort(x,decreasing,...)

`x`	Output from `cpg.perm`. Of class `"cpg.perm"`.
`save.plot`	Name of the file for the plot to be saved to. If not specified, plot will not be saved.
`file.type`	Type of file to be saved. Can either be `"pdf"` or `"eps"`. Selecting `file.type="eps"` will result in publication quality editable postscript files that can be opened by Adobe Illustrator or Photoshop.
`popup.pdf`	`TRUE` or `FALSE`. If creating a pdf file, this indicates if the plot should appear in a popup window as well. If running in a cluster-like environment, best to leave `FALSE`.
`main.title`	Main title to be put on the graph. If `NULL` one based on the analysis will be used
`eps.size`	Vector indicating the size of .eps file (if creating one). Correponds to the options horizontal and height in the `postscript` function.
`tplot`	Logical. If `TRUE`, ordered t-statistics will be plotted against their expected quanties. If `FALSE` (default), -log(p) will be plotted. If indep is a class variable this option will be ignored.
`perm.ci`	Logical. If `TRUE`, the confidence intervals computed will be from the permutated values, otherwise will be based on the theoretical values.
`classic`	Logical. If `TRUE`, a classic qq-plot will be generated, with all p-values plotted against predicted values (including significant). If `FALSE` Holm-significant CpG sites will not be used to compute expected quantiles and will be plotted separately.
`gc.p.val`	Logical. If true, plot will use the genomic control adjusted p-values.
`gcdisplay`	Logical.If true, plot will display the genomic control value in the legend.
`object`	Output of class `"cpg.perm"` from `"cpg.perm"`.
`decreasing`	logical. Should the sort be increasing or decreasing? Not available for partial sorting.
`...`	Arguments to be passed to methods, such as graphical parameters.

Empirical confidence intervals will be computed only if there are a hundred or more permutations. Otherwise the theoretical confidence intervals will be plotted.

Barfield, R.; Kilaru,V.; Conneely, K.
Maintainer: R. Barfield: <rbarfield01@fas.harvard.edu>

cpg.perm plot.cpg scatterplot manhattan cpg.assoc

data(samplecpg,samplepheno,package="CpGassoc")
##We will do the analysis on a subset to save time
###NOTE: If you are dealing with large data, do not specify large.data=FALSE.
###The default option is true.
##This will involve partitioning up the data and performing more gc() to clear up space
#The qq plot:
Testperm<-cpg.perm(samplecpg[1:300,],samplepheno$weight,seed=2314,nperm=10,large.data=FALSE)
plot(Testperm)
#The t-statistic plot from cpg.perm has confidence intervals since we were allowed 
#to perform permutations on the T-values.
plot(Testperm,tplot=TRUE)
#If there was 100 or more permutations, there would be emperical confidence intervals.

#Getting an example of the non classic QQ plot
plot(Testperm,classic=FALSE)


###Now for Sort
head(sort(Testperm)$results)
head(Testperm$results)