R/mIFTO.generate.pxp.image.data.R

In AstroPathJHU/mIFTO: mIFTO: Multiplex Immunoflourescence Titration Optimization

#########################generate.pxp.image.data################################
#
#'Used to create the pixel-by-pixel graph data and return a table;
#'Created By: Benjamin Green;
#'Last Edited 08/11/2020
#'
#'This function is desgined to do analysis for IF titration series
#'in Pixel by Pixel data provding output for each IMAGE individually
#'grouped by Concentration
#'
#'It is meant to be run through the RUN function
#'
#'
#' @param Concentration a numeric vector of concentrations used in the titration
#' @param x a unique identifier for the slide to be analyzed
#' @param y the numeric of which index from the concentration vector to use
#' @param q the image coordinates of the current image as a comma separated pair
#' @param Antibody_Opal the paired string for an antibody opal pair, designated
#' as "AB (Opal NNN)"
#' @param titration.type.name the type of titration that was performed
#' (TSA or Primary)
#' @param Thresholds a list of thresholds used for each concentration and slide
#' @param paths the paths to the data as a list, with an element for each
#' concentration
#' @param connected.pixels the number of pixels that a pixel must be connected
#' to for positivity measures
#' @param flowout logical for whether or not flow like results will be produced
#' @param Opal1 the opal value of interest
#' @param decile.logical whether or not to run a decile approach analysis
#' @param threshold.logical whether or not to run a threshold approach analysis
#' @param pb.Object
#' @return
#' @export
#'
mIFTO.generate.pxp.image.data <- function(
    Concentration, x, y, q, Antibody_Opal,
    titration.type.name, titration.type, Thresholds, paths,
    connected.pixels, flowout, Opal1,
    decile.logical, threshold.logical, pb.Object="") {
  #
  # this is the current image name
  #
  if (grepl("Primary", titration.type, fixed = TRUE)){
    str = paste0(
      '.*', x, '.*',titration.type.name, '_1to', Concentration[y], '.*Opal',Opal1,
      '_.*\\[',q, '\\]'
    )
  }
  if (grepl("Fluoro", titration.type, fixed = TRUE)){
    str = paste0(
      '.*', x, '.*','.*Opal',Opal1,'_1to', '.*', Concentration[y],
      '_.*\\[',q, '\\]'
    )
  }
  #
  # read that image in
  #
  data.in <- mIFTO::mIFTO.tiff.list(paths[[y]], pattern.in = str, Opal1=Opal1)

  err.val <- data.in$err.val
  if (err.val != 0){
    stop(err.val)
  }
  data.in <- data.in$data.out
  data.in <- data.in[[1]]
  nn <- names(data.in)
  d.v <- grep(Opal1, nn, value = T)
  #
  # measure crosstalk between channels
  #
  # create the flow output for this image
  #
  if (flowout == TRUE) {
    data.in.write <- vector('list',length(data.in))
    for (i1 in 1:length(data.in)) {
      data.in.write[[i1]] <- as.numeric(unlist(data.in[[i1]]))
    }
    names(data.in.write) <- names(data.in)
    str = paste0(
      wd,'/Results.pixels/data/raw/flow_like_tables/',
      Antibody_Opal,'_',x,'_1to',Concentration[y],'_[',q,'].csv')
    data.table::fwrite(data.in.write, file=str,sep=',')
  }
  #
  # select and store only the desired data
  #
  data.in <- data.in[[d.v]]
  #
  small.tables <- list()
  #
  if (decile.logical) {
    #
    decile.positivity.data <- mIFTO::mIFTO.decile.define.image.positivity(
      data.in, 10)
    small.tables <- c(
      small.tables,'decile.SN.Ratio' =
        list(mIFTO::mIFTO.sn.ratio.calculations(
          decile.positivity.data,Concentration[y],x,q)),'decile.T.Tests' =
        list(mIFTO::mIFTO.welch.t.test.calculations(
          decile.positivity.data,Concentration[y],x,q)),'decile.Image' =
        list(decile.positivity.data)
    )
  }
  #
  if (threshold.logical) {
    #
    # get the positvity data
    #
    if ((length(connected.pixels) == 1) & ('NA' %in% connected.pixels)) {
      positivity.data <- mIFTO::mIFTO.define.image.positivity(
        data.in,Thresholds[[x]][y],connected.pixels)
    } else {
      tryCatch({
        positivity.data <- mIFTO::mIFTO.define.image.positivity(
          data.in,Thresholds[[x]][y],connected.pixels[[x]][y])
      }, error=function(cond){
        return(cond)
      })
    }
    #
    # do the calculations for each type of graph and store
    #
    tryCatch({
      small.tables<-c(
        small.tables,'SN.Ratio' =
          list(mIFTO::mIFTO.sn.ratio.calculations(
            positivity.data,Concentration[y],x,q)),'T.Tests' =
          list(mIFTO::mIFTO.welch.t.test.calculations(
            positivity.data,Concentration[y],x,q)),'Image.ID' =
          paste0('[',q,']'),'Image' = list(positivity.data))
    }, warning = function(cond) {
      # if (typeof(pb.Object) != "character"){
      #   modal_out <- shinyalert::shinyalert(
      #     title = paste0('Warning in small.tables for ',
      #                    x, ' 1to', Concentration[y], '[', q, ']'),
      #     text = paste0('Please check the computer resources, slide names, ',
      #                   'image layers correspond to protocol type, ',
      #                   'and that component data tiffs for ', x,
      #                   ' 1to',Concentration[[y]], '[', q, ']',' exist. Then contact ',
      #                   'Sigfredo Soto at ssotodi1@jh.edu for assistance.',
      #                   cond),
      #     type = 'error',
      #     showConfirmButton = TRUE
      #   )
      # }
      stop(cond)
    }, error = function(cond) {
      # if (typeof(pb.Object) != "character") {
      #   modal_out <- shinyalert::shinyalert(
      #     title = paste0('Error in small.tables for ',
      #                    x, ' 1to', Concentration[y], '[', q, ']'),
      #     text = paste0('Please check the computer resources, slide names, ',
      #                   'image layers correspond to protocol type, ',
      #                   'and that component data tiffs for ', x,
      #                   ' 1to',Concentration[[y]], '[', q, ']',' exist. Then contact ',
      #                   'Sigfredo Soto at ssotodi1@jh.edu for assistance.',
      #                   cond),
      #     type = 'error',
      #     showConfirmButton = TRUE
      #   )
      # }
      stop(cond)
    }, finally = {})
    #
    rm(positivity.data)
  } else {
    small.tables <- c(
      small.tables,
      'Image' = as.vector(data.in)
    )
  }
  #
  rm(data.in)
  return(small.tables)
}