Modified example of code provided in https://support.bioconductor.org/p/115224/ to identify error thrown by EBImage

IF015_example.R

WD <- tempdir()
setwd(WD)
library(EBImage)
library(tidyverse)

## download example zip file ad unpack
download.file('https://www.dropbox.com/s/40e5tfohgdm9wlo/IF015_plate002_test.zip?dl=1',
              destfile = 'IF015_plate002.zip', mode = "wb")
unzip('IF015_plate002.zip')

# Parameters
IF = "IF015_noSpeck"

# List of files########################################################
AllImages <- as.data.frame(list.files(getwd(), recursive = T, pattern = '.tif$'), col.names = 'FileNames')
colnames(AllImages)[1] <- 'FileNames'

# Extract Metainformation##############################################################################
MetaInformation <- function(Files, Path){
  Files$Directory <- Path
  Files$Plate <- substring(Files$FileNames,12,14) ## Plate
  Files$Plate <- as.numeric(Files$Plate)
  Files$Stack <- sub(".*test/", "", Files$FileNames) ## Stack
  Files$DataStack <- substring(Files$Stack,0,35) ## DataStack
  Files$ID <- sub("--W.*", "", Files$Stack) ## ID
  Files$Well <- sub(".*--W", "", Files$Stack) ## W #
  Files$Well <- substring(Files$Well,0,5) ## W #
  Files$Position <- sub(".*--P", "", Files$Stack) ## Position
  Files$Position <- substring(Files$Position,0,5) ## Position
  Files$Time <- sub(".*--T", "", Files$Stack) ## Time
  Files$Time <- substring(Files$Time,0,5) ## Time
  Files$Channel <- sub(".*--", "", Files$Stack) ## Channel
  Files$Channel <- sub(".tif.*", "", Files$Channel) ## Channel
  return(as.data.frame(Files))
}

# Add metainformation (if necessary, more revelant for data analysis)############
IdToMap <- function(FileList){
  rN = c(1:16)
  cN = c(1:24)
  cID = c(1:24)
  rID = c('A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P')
  Row <- data.frame(rID, rN)
  ID = data.frame(cID, cN)
  ID$rID <- NA
  for(i in rID){
    IDtemp <- ID[1:24,]
    IDtemp$rID <- as.character(i) 
    ID <- rbind(ID, IDtemp)
  }
  ID <- merge(ID[25:nrow(ID),], Row, by = "rID", all.x = T)
  ID$ID <- paste(ID$rID, ID$cID, sep = "")
  FileList <- merge(x = FileList, y = ID, by = c("ID"), all.x = T)
}

AllImages <- MetaInformation(Files = AllImages, Path = WD)
AllImages <- IdToMap(AllImages)
unique(AllImages$Plate)
str(AllImages)

# Read images and extract features#####################
ImageProcessing <- function(Image, Plate, Well, Position){
  #---------------Rescale pixel intensity----------
  Bottom = 2^15/(2^16-1) 
  Top = (2^15+4095)/(2^16-1)
  Rescale <- function(x){
    (x - Bottom) / (Top - Bottom)   
  }
  
  Boolean <-  AllImages$Plate == Plate & AllImages$ID == Well & AllImages$Position == Position
  
  #---------------Load Images------------------------
  Img405 = readImage(paste0(AllImages[AllImages$Channel == "DAPI" & Boolean, "Directory"],
                            "/",
                            AllImages[AllImages$Channel == "DAPI" & Boolean, "FileNames"]))
  Img405 = Rescale(Img405)
  NImg405 = EBImage::normalize(Img405, inputRange = c(range(Img405)[1], range(Img405)[2]))
  Img488 = readImage(paste0(AllImages[AllImages$Channel == "GFP" & Boolean, "Directory"],
                            "/",
                            AllImages[AllImages$Channel == "GFP" & Boolean, "FileNames"]))
  Img488 = Rescale(Img488)
  NImg488 = EBImage::normalize(Img488)
  Img568 = readImage(paste0(AllImages[AllImages$Channel == "mCherry" & Boolean, "Directory"], 
                            "/",
                            AllImages[AllImages$Channel == "mCherry" & Boolean, "FileNames"]))
  Img568 = Rescale(Img568)
  NImg568 = EBImage::normalize(Img568, inputRange = c(range(Img568)[1], range(Img568)[2]))
  Img647 = readImage(paste0(AllImages[AllImages$Channel == "647" & Boolean, "Directory"], 
                            "/",
                            AllImages[AllImages$Channel == "647" & Boolean, "FileNames"]))
  Img647 = Rescale(Img647)
  NImg647 = EBImage::normalize(Img647, inputRange = c(range(Img647)[1], range(Img647)[2]))
  #---------------smooth and threshold nuleus------------------------------
  FilterNuc = makeBrush(size = 51, shape = "gaussian", sigma=2)
  Img405smooth = filter2(Img405, filter = FilterNuc)
  nucThrManual = thresh(Img405smooth, w = 100, h = 100, offset = 0.0005)
  nucOpening = opening(nucThrManual, kern = makeBrush(15, shape="disc"))
  nucSeed = bwlabel(nucOpening)
  nucFill = fillHull(thresh(Img405smooth, w = 20, h = 20, offset = 0.01))
  nucRegions = propagate(Img405smooth, nucSeed, mask = nucFill)
  nucMask = watershed(distmap(nucOpening), tolerance = 1, ext = 1)
  
  #------------------Generate voronoi-------------------------------------
  VoR = propagate(nucMask, nucMask, lambda = 100000)
  #------------------Generate donut and bubble for proxy Cytoplasm -------
  Bubble = dilate(nucRegions, kern = makeBrush(15, shape = 'disc'))
  display(colorLabels(Bubble))
  BubbleBound = propagate(Bubble, nucMask, Bubble, lambda = 1000)
  Donut = BubbleBound - nucMask

  #---------------Features extraction-------------------------------------------------------------------------
  F405_Nuc = computeFeatures(nucMask, Img405, xname = "Nuc", refnames = "405", haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F488_Nuc = computeFeatures(nucMask, Img488, xname = "Nuc", refnames = "488", haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F488_Donut = computeFeatures(Donut, Img488, xname = "Donut", refnames = "488", haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F488_Bubble = computeFeatures(BubbleBound, Img488, xname = "Bubble", refnames = "488", haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  
  F568_Nuc = computeFeatures(nucMask, Img568, xname = "Nuc", refnames = "568",haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F568_Donut = computeFeatures(Donut, Img568, xname = "Donut", refnames = "568",haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F568_Bubble = computeFeatures(BubbleBound, Img568, xname = "Donut", refnames = "568",haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  
  F647_Nuc = computeFeatures(nucMask, Img647, xname = "Nuc", refnames = "647",haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F647_Donut = computeFeatures(Donut, Img647, xname = "Donut", refnames = "647",haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  F647_Bubble = computeFeatures(BubbleBound, Img647, xname = "Donut", refnames = "647",haralick.nbins = 32, haralick.scales = c(1,2,4,8))
  
  Fc = cbind(F405_Nuc, 
             F488_Nuc,
             F488_Donut, 
             F488_Bubble, 
             F568_Nuc,
             F568_Donut,
             F568_Bubble,
             F647_Nuc,
             F647_Donut,
             F647_Bubble)
  Fc = as.data.frame(Fc) %>% rownames_to_column

  #---------------Remove cells at the edge-------------------------------------------------------------------------------
  #subset for boundary pixels
  dims = dim(nucMask) 

  border = c(nucMask[1:dims[1],1],
             nucMask[1:dims[1],dims[2]],
             nucMask[1,1:dims[2]],
             nucMask[dims[1],1:dims[2]]
  )
  #extract object identifiers at the boundary
  ids = unique(border[which(border != 0)])
  Fc = filter(Fc, !rowname %in% ids)
  
  if (nrow(Fc) == 0) {
    Fc = data.frame(0, nrow = 0, ncol = 141*12+1)
  }
  
  write.csv(Fc, paste0(IF,"_p--",Plate,"_w--",Well,"_pos--",Position,".csv"))
}

#----------------Run ImageProcessing() to everyfield---------------------------------------------------------------------
for (Plate in unique(AllImages$Plate)) {
  for(Well in unique(AllImages$ID)) {
    for(Position in unique(AllImages$Position)) {
      
      ImageProcessing(Image = AllImages, Plate = Plate, Well = Well, Position = Position)
      
      print(paste0("Plate: ", Plate, "; Well: ", Well, "; Position: ", Position, "; Time:", Sys.time()))
      
    }
  }
}