#' @export
#'
#' @title pipeline with report generation
#' @description
#' Loads user's data, prompt a graphical representation of a 96
#' well plate and let the user select where the duplicates of each
#' condition were placed. Use for reordering excel file.
#' Plate image with selection can also be saved in the form of a png
#' file in the output_MQ directory.
#'
#' Also generates a complete report with the graphics
#' @import prettydoc
#'
#' @name pipeline
#' @rdname pipeline
#' @aliases pipeline
#' @usage
#' pipeline(filepath,sheet_name=NULL,number_of_replicates,number_of_conditions,
#' control=FALSE,save.files=TRUE,MACSQuant.obj=NULL)
#' @param filepath path of the excel file
#' @param sheet_name Name of the sheet to load
#' (optional, first sheet is default)
#' @param number_of_replicates For each condition, the number of duplicates
#' (must be the same for all conditions)
#' @param number_of_conditions The number of conditions tested
#' (eg: Drug 1 alone, Drug 2 alone)
#' @param control Is there a control in this experiment (eg: Staurosporin)
#' @param save.files Used to save the image in the output folder
#' @param MACSQuant.obj object of class MACSQuant
#'
#' @examples
#' print("run manually, requires user input")
#' filepath <- system.file("extdata", "SingleDrugs.xlsx",
#' package = "MACSQuantifyR")
#' # pipeline(filepath,3,5)
#' # let you select 5 conditions of 3 replicates each
#' @return A formatted report file along with intermediates results
# source("./R/load_MACSQuant.R")
# source("./R/on_plate_selection.r")
pipeline <- function(filepath, sheet_name = NULL,
number_of_replicates,
number_of_conditions,
control = FALSE,
save.files = TRUE,
MACSQuant.obj = NULL) {
MACSQuant <- load_MACSQuant.internal(filepath, sheet_name, MACSQuant.obj)
MACSQuant <- on_plate_selection.internal(MACSQuant,
number_of_replicates,
number_of_conditions,
control,
save.files)
if (save.files == TRUE) {
generate_report(MACSQuant)
}
return(MACSQuant)
}
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