R/lqmodelFit.R

In PickeringLab/CellSurvAssay: Clonogenic Survival Analysis in R made easy!

#' Fits the Linear Quadratic Model
#'
#' It helps fit the linear quadratic model using the
#' \code{\link[CFAssay:cellsurvLQfit]{cellsurvLQfit}} function of the CFAssay
#' package, but automates the data wrangling steps, thus making it more
#' convenient to use for beginner R users. Visit
#' \url{https://bioconductor.org/packages/release/bioc/html/CFAssay.html} for
#' more details about the method of the fit.
#'
#' @param data A data frame containing at least the following five columns with
#'   these exact names: "cline", "Exp", "dose", "ncells", "ncolonies".
#' @param ctype Name of the cell-line/group for which the model is to be fit.
#' @param method Method used for the fit. It's \code{"ml"} (maximum likelihood)
#'   by default. Also accepts \code{"ls"} (least squares) or \code{"franken"}
#'   (weighted least squares as described by Franken eta al.(2006)).
#' @param PEmethod Controls the value of the plating efficiencies. \code{"fit"}
#'   calculates fitted plating efficiencies as model parameters, \code{"fix"}
#'   uses fixed ones calculated from the observed zero dose data.
#' @return An object of class \code{cellsurvLQfit}, as returned by
#'   \code{\link[CFAssay:cellsurvLQfit]{cellsurvLQfit}}.
#' @examples
#' datatab <- CASP8_data
#' lqmodelFit(datatab, "control-B")
#' lqmodelFit(datatab, "control-B", method = "ls", PEmethod = "fix")
#' @export
lqmodelFit <- function(data, ctype, method = "ml", PEmethod = "fit") {
  invisible(utils::capture.output(fit <- CFAssay::cellsurvLQfit(subset(data, cline == ctype), method = method, PEmethod = PEmethod)))
  intro <- paste0("****** Cell type: ", ctype, " ******\n\n")
  end <- paste0("\n*** Analysis by CellSurvAssay v", utils::packageVersion("CellSurvAssay"), " ***")
  cat(intro)
  print(fit)
  cat(end)
}