R/qqDMCs-method.R

In DMCHMM: Differentially Methylated CpG using Hidden Markov Model

.qqDMCs <- function(object, ...) {

    if (is.null(metadata(object)$DMCHMM))
        stop("Input must be an object
    obtianed from findDMCs method.")

    pvector <- metadata(object)$DMCHMM$pvalues
    # limit to not missing, not nan, not null, not infinite, between 0 and
    # 1
    pvector <- pvector[!is.na(pvector) & !is.nan(pvector) & !is.null(pvector) &
        is.finite(pvector) & pvector < 1 & pvector > 0]

    # Observed and expected
    o = -log10(sort(pvector, decreasing = FALSE))
    e = -log10(ppoints(length(pvector)))


    # The new way to initialize the plot.  See
    # http://stackoverflow.com/q/23922130/654296 First, define your default
    # arguments
    def_args <- list(pch = 20, xlim = c(0, max(e)), ylim = c(0, max(o)),
        xlab = expression(Expected ~ ~-log[10](italic(p))),
        ylab = expression(Observed ~
            ~-log[10](italic(p))))
    ## Next, get a list of ... arguments dotargs <-
    ## as.list(match.call())[-1L]
    dotargs <- list(...)
    ## And call the plot function passing NA, your ...  arguments, and the
    ## default arguments that were not defined in the ...  arguments.
    tryCatch(do.call("plot", c(list(x =e, y = o), def_args[!names(def_args) %in%
        names(dotargs)], dotargs)), warn = stop)

    # Add diagonal
    abline(0, 1, col = "red")

}

#' @rdname qqDMCs-method
#' @aliases qqDMCs-method qqDMCs
setMethod("qqDMCs", signature(object = "BSDMCs"), .qqDMCs)