R/sc1_mthds.R

In philipmorrisintl/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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#-------------------------------------------------------------------------------
# sc1_mthds: Load list of sc1 method functions
#-------------------------------------------------------------------------------

#' @name SC1_Methods
#' @title List of level 1 single-concentration normalization functions
#'
#' @description
#' \code{sc1_mthds} returns a list of functions to be used during level 1
#' single-concentration processing.
#'
#' @return A list functions
#'
#' @seealso \code{\link{sc1}}, \code{\link{Method functions}} to query what
#' methods get applied to each acid
#'
#' @details
#' The functions contained in the list returned by \code{sc1_mthds} return
#' a list of expressions to be executed in the \code{sc2} (not exported)
#' function environment. The functions are described here for reference
#' purposes, The \code{sc1_mthds} function is not exported, nor is it
#' intended for use.
#'
#' All available methods are described in the Available Methods section, listed
#' by the function/method name.
#'
#' @section Available Methods:
#'
#' The methods are broken into three types, based on what fields they define.
#' Different methods are used to define "bval" (the baseline value), "pval"
#' (the positive control value), and "resp" (the final response value).
#'
#' Although it does not say so specifically in each description, all methods
#' are applied by acid.
#'
#' More information about the level 3 single-concentration processing is
#' available in the package vignette, "Pipeline_Overview."
#'
#' \subsection{bval Methods}{
#'   \describe{
#'     \item{bval.apid.nwlls.med}{Calculate bval as the median of rval for
#'     wells with wllt equal to "n," by apid.}
#'     \item{bval.apid.twlls.med}{Calculate bval as the median of rval for
#'     wells with wllt equal to "t," by apid.}
#'     \item{bval.apid.tn.med}{Calculate bval as the median of rval for wells
#'     with wllt equal to "t" or "n," by apid.}
#'   }
#' }
#'
#' \subsection{pval Methods}{
#'   \describe{
#'     \item{pval.apid.pwlls.med}{Calculate pval as the median of rval for
#'     wells with wllt equal to "p," by apid.}
#'     \item{pval.apid.mwlls.med}{Calculate pval as the median of rval for
#'     wells with wllt equal to "m," by apid.}
#'     \item{pval.apid.medpcbyconc.max}{First calculate the median of rval for
#'     wells with wllt equal to "p" or "c," by wllt, conc, and apid. Then
#'     calculate pval as the maximum of the calculated medians, by apid.}
#'     \item{pval.apid.medpcbyconc.min}{First calculate the median of rval for
#'     wells with wllt equal to "p" or "c," by wllt, conc, and apid. Then
#'     calculate pval as the minimum of the calculated medians, by apid.}
#'     \item{pval.apid.medncbyconc.min}{First calculate the median of rval for
#'     wells with wllt equal to "m" or "o," by wllt, conc, and apid. Then
#'     calculate pval as the minimum of the calculated medians, by apid.}
#'     \item{pval.zero}{Define pval as 0.}
#'   }
#' }
#'
#' \subsection{resp Methods}{
#'   \describe{
#'     \item{resp.pc}{Calculate resp as \eqn{\frac{\mathit{rval} -
#'     \mathit{bval}}{\mathit{pval} - \mathit{bval}}100}{(rval - bval)/(pval
#'     - bval)*100}.}
#'     \item{resp.fc}{Calculate resp as \eqn{\mathit{rval}/\mathit{bval}}{
#'     rval/bval}.}
#'     \item{resp.logfc}{Calculate resp as \eqn{\mathit{rval} - \mathit{bval}}{
#'     rval - bval}.}
#'     \item{resp.log2}{Take the logarithm of resp with base 2.}
#'     \item{resp.multneg1}{Multiply resp by -1.}
#'     \item{none}{Do no normalization; make resp equal to rval.}
#'   }
#' }
#'
#' @keywords internal
#' 
#' @note
#' This function is not exported and is not intended to be used by the user.


sc1_mthds <- function() {

    list(

        bval.apid.nwlls.med=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    bval := median(
                        rval[wllt == "n"], na.rm=TRUE
                    ),
                    by=list(aeid, apid)]
            )
            list(e1)

        },

        bval.apid.twlls.med=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    bval := median(
                        rval[wllt == "t"], na.rm=TRUE
                    ),
                    by=list(aeid, apid)]
            )
            list(e1)

        },

        bval.apid.tn.med=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    bval := median(
                        rval[wllt %in% c("t", "n")],
                        na.rm=TRUE
                    ),
                    by=list(aeid, apid)]
            )
            list(e1)

        },

        pval.apid.pwlls.med=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    pval := median(
                        rval[wllt == "p"], na.rm=TRUE
                    ),
                    by=list(aeid, apid)]
            )
            list(e1)

        },

        pval.apid.or.aeid.pwlls.med=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    pval := median(
                        rval[wllt == "p"], na.rm=TRUE
                    ),
                    by=list(aeid, apid)]
            )
            e2 <- bquote(
                dat[J(.(aeids)),
                    temp := median(
                        pval,
                        na.rm=TRUE
                    ),
                    by=list(aeid)]
            )
            e3 <- bquote(
                dat[aeid %in% .(aeids) & (is.na(pval) | is.infinite(pval)),
                    pval := temp,
                    by=list(aeid)]
            )
            e4 <- bquote(dat[ , temp := NULL])
            list(e1,e2,e3,e4)

        },

        pval.apid.mwlls.med=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    pval := median(
                        rval[wllt == "m"], na.rm=TRUE
                    ),
                    by=list(aeid, apid)]
            )
            list(e1)

        },

        pval.apid.medpcbyconc.max=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    temp := median(
                        rval[wllt %in% c("c", "p")],
                        na.rm=TRUE
                    ),
                    by=list(aeid, apid, wllt, conc)]
            )
            e2 <- bquote(
                dat[J(.(aeids)),
                    pval := max(temp, na.rm=TRUE),
                    by=list(aeid, apid)]
            )
            e3 <- bquote(dat[ , temp := NULL])
            list(e1, e2, e3)

        },

        pval.apid.medpcbyconc.min=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    temp := median(
                        rval[wllt %in% c("c", "p")],
                        na.rm=TRUE
                    ),
                    by=list(aeid, apid, wllt, conc)]
            )
            e2 <- bquote(
                dat[J(.(aeids)),
                    pval := min(temp, na.rm=TRUE),
                    by=list(aeid, apid)]
            )
            e3 <- bquote(dat[ , temp := NULL])
            list(e1, e2, e3)

        },

        pval.apid.medncbyconc.min=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    temp := median(
                        rval[wllt %in% c("m","o")],
                        na.rm=TRUE
                    ),
                    by=list(aeid, apid, wllt, conc)]
            )
            e2 <- bquote(
                dat[J(.(aeids)),
                    pval := min(temp, na.rm=TRUE),
                    by=list(aeid, apid)]
            )
            e3 <- bquote(dat[ , temp := NULL])
            list(e1, e2, e3)

        },

        pval.zero=function(aeids) {

            e1 <- bquote(dat[J(.(aeids)), pval := 0])
            list(e1)

        },

        resp.pc=function(aeids) {

            e1 <- bquote(
                dat[J(.(aeids)),
                    resp := (rval - bval)/(pval - bval)*100]
            )
            list(e1)

        },

        resp.fc=function(aeids) {

            e1 <- bquote(dat[J(.(aeids)), resp := rval/bval])
            list(e1)

        },

        resp.logfc=function(aeids) {

            e1 <- bquote(dat[J(.(aeids)), resp := rval - bval])
            list(e1)

        },

        resp.log2=function(aeids) {

            e1 <- bquote(dat[J(.(aeids)), resp := log2(resp)])
            list(e1)

        },

        none=function(aeids) {

            e1 <- bquote(dat[J(.(aeids)), resp := rval])
            list(e1)

        },

        resp.multneg1=function(aeids) {

            e1 <- bquote(dat[J(.(aeids)), resp := resp * -1])
            list(e1)

        }

    )
}

#-------------------------------------------------------------------------------