R/mc5_mthds.R

In GladiaTOX: R Package for Processing High Content Screening data

#####################################################################
## This program is distributed in the hope that it will be useful, ##
## but WITHOUT ANY WARRANTY; without even the implied warranty of  ##
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the    ##
## GNU General Public License for more details.                    ##
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#-------------------------------------------------------------------------------
# mc5_mthds: Load list of cutoff methods (to be used at level 5)
#-------------------------------------------------------------------------------

#' @name MC5_Methods
#' @title Load list of level 5 multiple-concentration cutoff methods
#'
#' @description
#' \code{mc5_mthds} returns a list of additional activity cutoff methods
#' to be used during level 5 multiple-concentration processing.
#'
#' @return A list of functions
#'
#' @keywords internal
#' 
#' @seealso \code{\link{mc5}}, \code{\link{Method functions}} to query what
#' methods get applied to each aeid
#'
#' @section Available Methods:
#'
#' More information about the level 5 multiple-concentration processing is
#' available in the package vignette, "Pipeline_Overview."
#'
#' \describe{
#'   \item{bmad3}{Add a cutoff value of 3*bmad.}
#'   \item{pc20}{Add a cutoff value of 20.}
#'   \item{log2_1.2}{Add a cutoff value of log2(1.2).}
#'   \item{log10_1.2}{Add a cutoff value of log10(1.2).}
#'   \item{bmad5}{Add a cutoff value of 5*bmad.}
#'   \item{bmad6}{Add a cutoff value of 6*bmad.}
#'   \item{bmad10}{Add a cutoff value of 10*bmad.}
#'   \item{log2_2}{Add a cutoff value of log2(2).}
#'   \item{log10_2}{Add a cutoff value of log10(2).}
#'   \item{neglog2_0.88}{Add a cutoff value of -1*log2(0.88).}
#'   \item{vmad3}{Add a cutoff value of 3*vmad.}
#'   \item{vmad5}{Add a cutoff value of 5*vmad.}
#'   \item{vmad10}{Add a cutoff value of 10*vmad.}
#' }


mc5_mthds <- function() {

    list(

        bmad3=function() {

            e1 <- bquote(coff <- c(coff, dat[ , unique(bmad)*3]))
            list(e1)

        },

        pc20=function() {

            e1 <- bquote(coff <- c(coff, 20))
            list(e1)

        },

        log2_1.2=function() {

            e1 <- bquote(coff <- c(coff, log2(1.2)))
            list(e1)

        },

        log10_1.2=function() {

            e1 <- bquote(coff <- c(coff, log10(1.2)))
            list(e1)

        },

        bmad5=function() {

            e1 <- bquote(coff <- c(coff, dat[ , unique(bmad)*5]))
            list(e1)

        },

        bmad6=function() {

            e1 <- bquote(coff <- c(coff, dat[ , unique(bmad)*6]))
            list(e1)

        },

        bmad10=function() {

            e1 <- bquote(coff <- c(coff, dat[ , unique(bmad)*10]))
            list(e1)

        },

        maxmed20pct=function() {

            e1 <- bquote(coff <- c(coff, dat[ , max(max_med)*.20]))
            list(e1)

        },

        pc70=function() {

            e1 <- bquote(coff <- c(coff, 70))
            list(e1)

        },

        pc50=function() {

            e1 <- bquote(coff <- c(coff, 50))
            list(e1)

        },

        log2_2=function() {

            e1 <- bquote(coff <- c(coff, log2(2)))
            list(e1)

        },

        log10_2=function() {

            e1 <- bquote(coff <- c(coff, log10(2)))
            list(e1)

        },

        neglog2_0.88=function() {

            e1 <- bquote(coff <- c(coff, -1*log2(0.88)))
            list(e1)

        },

        vmad3=function() {
            e1 <- bquote(coff <- c(coff, 3*gtoxLoadVmad(aeid=ae)$vmad))
            list(e1)
        },

        vmad5=function() {
            e1 <- bquote(coff <- c(coff, 5*gtoxLoadVmad(aeid=ae)$vmad))
            list(e1)
        },

        vmad10=function() {
            e1 <- bquote(coff <- c(coff, 10*gtoxLoadVmad(aeid=ae)$vmad))
            list(e1)
        }

    )
}

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