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

Description Usage Arguments Value Note Author(s) See Also Examples

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

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

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

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

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

`x`	Output of class `"cpg"` from cpg.assoc or cpg.work.
`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`.
`tplot`	Logical. If `TRUE`, t-statistics will be plotted vs. their expected quantiles. If `FALSE` (default), -log(p) will be plotted. (Note: if `class(x$indep)=='factor'` this option will be ignored.)
`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.
`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.
`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"` from `cpg.assoc` or `cpg.work`.
`decreasing`	logical. Should the sort be increasing or decreasing? Not available for partial sorting.
`...`	Arguments to be passed to methods, such as graphical parameters.

sort.cpg returns an item of class "cpg" that is sorted by p-value. summary.cpg creates a qq-plot based on the data, and scatterplots or boxplots for the top sites.

Plots with empirical confidence intervals based on permutation tests can be obtained from cpg.perm. See plot.cpg.perm for more info.

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

cpg.perm cpg.assoc scatterplot manhattan plot.cpg.perm

##Using the results from the example given in cpg.assoc.
###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
##QQ Plot:
data(samplecpg,samplepheno,package="CpGassoc")
test<-cpg.assoc(samplecpg,samplepheno$weight,large.data=FALSE)
plot(test)
##t-statistic plot:
plot(test,tplot=TRUE)


#Getting our plot:
plot(test,classic=FALSE)


##Now an example of sort
head(sort(test)$results)

##Summary
summary(test)

Loading required package: nlme
     CPG.Labels T.statistic      P.value Holm.sig       FDR   gc.p.value
694      CpG694    3.454271 0.0006456268    FALSE 0.4318310 0.0006456268
293      CpG293    3.412320 0.0007485123    FALSE 0.4318310 0.0007485123
560      CpG560    3.313353 0.0010549618    FALSE 0.4318310 0.0010549618
148      CpG148    3.133454 0.0019286973    FALSE 0.5645412 0.0019286973
998      CpG998   -3.079596 0.0022986204    FALSE 0.5645412 0.0022986204
1059    CpG1059   -2.883525 0.0042668430    FALSE 0.7693539 0.0042668430

The top ten CpG sites were:
     CPG.Labels T.statistic      P.value Holm.sig       FDR   gc.p.value
694      CpG694    3.454271 0.0006456268    FALSE 0.4318310 0.0006456268
293      CpG293    3.412320 0.0007485123    FALSE 0.4318310 0.0007485123
560      CpG560    3.313353 0.0010549618    FALSE 0.4318310 0.0010549618
148      CpG148    3.133454 0.0019286973    FALSE 0.5645412 0.0019286973
998      CpG998   -3.079596 0.0022986204    FALSE 0.5645412 0.0022986204
1059    CpG1059   -2.883525 0.0042668430    FALSE 0.7693539 0.0042668430
1182    CpG1182   -2.819710 0.0051827097    FALSE 0.7693539 0.0051827097
100      CpG100    2.787987 0.0057015107    FALSE 0.7693539 0.0057015107
751      CpG751   -2.759379 0.0062093208    FALSE 0.7693539 0.0062093208
238      CpG238    2.756367 0.0062650966    FALSE 0.7693539 0.0062650966

To access results for all  1228  CpG sites use object$results 
or sort(object)$results to obtain results sorted by p-value.

General info:
  Min.P.Observed Num.Cov fdr.cutoff FDR.method Phenotype chipinfo num.Holm
1   0.0006456268       0       0.05         BH    weight     NULL        0
  num.fdr
1       0

0 sites were found significant by the Holm method
0 sites were found significant by BH method

The beta values were taken from: samplecpg 
Effect sizes and standard error can be accessed using $coefficients
Other attributes are: results, Holm.sig, FDR.sig, info, indep, covariates, chip 
 They can be accessed using the $