New version 0.1.8: include a third protein color for a protein in the…

… cytosol and finde the outline of the cell
SFB-ELAINE · Jan 11, 2021 · a86f0ff · a86f0ff
1 parent f95eadb
commit a86f0ff
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Showing 5 changed files with 137 additions and 10 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: cellPixels
 Type: Package
 Title: Detect neclei and count pixels within and outside these
-Version: 0.1.7
+Version: 0.1.8
 Author: c(person("Kai", "Budde", email = "kai.budde@uni-rostock.de",
    role = c("aut", "cre"))
 Maintainer: Kai Budde <kai.budde@uni-rostock.de>

diff --git a/R/cellPixels.R b/R/cellPixels.R
@@ -10,6 +10,8 @@
 #' @param nucleus_color A character (color (layer) of nuclei)
 #' @param protein_in_nuc_color A character (color (layer) of protein
 #' expected in nucleus)
+#' @param protein_in_cytosol_color A character (color (layer) of protein
+#' expected in cytosol)
 #' @param number_size_factor A number (factor to resize numbers for
 #' numbering nuclei)
 #' @param bit_depth A number (bit depth of the original czi image)
@@ -20,6 +22,7 @@
 cellPixels <- function(input_dir = NULL,
                        nucleus_color = "blue",
                        protein_in_nuc_color = "none",
+                       protein_in_cytosol_color = "none",
                        number_size_factor = 0.2,
                        bit_depth = NULL,
                        number_of_pixels_at_border_to_disregard = 3) {
@@ -86,8 +89,10 @@ cellPixels <- function(input_dir = NULL,
     "dimension_x" = rep(NA, number_of_czis),
     "dimension_y" = rep(NA, number_of_czis),
     "number_of_nuclei" = rep(NA, number_of_czis),
-    "color_of_second_proteins_in_nuclei" = rep(NA, number_of_czis),
+    "color_of_second_protein_in_nuclei" = rep(NA, number_of_czis),
     "number_of_nuclei_with_second_protein" = rep(NA, number_of_czis),
+    "color_of_third_protein_in_cytosol" = rep(NA, number_of_czis),
+    "number_of_cells_with_third_protein" = rep(NA, number_of_czis),
     "intensity_sum_red_full" = rep(NA, number_of_czis),
     "intensity_sum_green_full" = rep(NA, number_of_czis),
     "intensity_sum_blue_full" = rep(NA, number_of_czis),
@@ -362,7 +367,7 @@ cellPixels <- function(input_dir = NULL,
     # barplot(table(nmask)[-1])
 
     table_nmask <- table(nmask)
-    nuc_min_size <- 0.05*stats::median(table_nmask[-1])
+    nuc_min_size <- 0.1*stats::median(table_nmask[-1])
 
     # remove objects that are smaller than min_nuc_size
     to_be_removed <- as.integer(names(which(table_nmask < nuc_min_size)))
@@ -472,8 +477,14 @@ cellPixels <- function(input_dir = NULL,
       Image_protein_in_nuc <- EBImage::gblur(Image_protein_in_nuc, sigma = 7)
       #display(Image_protein_in_nuc)
 
+
       # Mask the proteins within the nucleus
-      pmask <- EBImage::thresh(Image_protein_in_nuc, w=15, h=15, offset=0.07)
+      if(grepl(pattern = "_20x_", file_names[i])){
+        # Smaller moving rectangle if the magnification is 20x (instead of 40x)
+        pmask <- EBImage::thresh(Image_protein_in_nuc, w=15, h=15, offset=0.07)
+      }else{
+        pmask <- EBImage::thresh(Image_protein_in_nuc, w=35, h=35, offset=0.07)
+      }
 
       # Morphological opening to remove objects smaller than the structuring element
       pmask <- EBImage::opening(pmask, EBImage::makeBrush(5, shape='disc'))
@@ -510,6 +521,95 @@ cellPixels <- function(input_dir = NULL,
 
     }
 
+    # Count the number of cells that contain a third colored protein  ------
+
+    if(!is.null(protein_in_cytosol_color) & protein_in_cytosol_color != "none"){
+
+
+      # Save only color layer of the second protein colored
+      image_protein_in_cytosol <- getLayer(
+        image = image_loaded, layer = protein_in_cytosol_color)
+
+      Image_protein_in_cytosol <- EBImage::Image(image_protein_in_cytosol)
+      rm(image_protein_in_cytosol)
+      #display(Image_protein_in_cytosol)
+
+      # Blur the image
+      Image_protein_in_cytosol <- EBImage::gblur(Image_protein_in_cytosol, sigma = 5)
+      #display(Image_protein_in_nuc)
+
+      # Mask the proteins within the cytosol
+      if(grepl(pattern = "_20x_", file_names[i])){
+        # Smaller moving rectangle if the magnification is 20x (instead of 40x)
+        cytosolmask <- EBImage::thresh(Image_protein_in_cytosol, w=100, h=100, offset=0.01)
+      }else{
+        cytosolmask <- EBImage::thresh(Image_protein_in_cytosol, w=200, h=200, offset=0.01)
+      }
+
+      #display(cytosolmask)
+
+      # Morphological opening to remove objects smaller than the structuring element
+      cytosolmask <- EBImage::opening(cytosolmask, EBImage::makeBrush(5, shape='disc'))
+      # Fill holes
+      cytosolmask <- EBImage::fillHull(cytosolmask)
+      #display(cytosolmask)
+
+      # Keep only those cell bodies that contain a nucleus
+      cytosolmask <- EBImage::bwlabel(cytosolmask)
+      no_of_cytosols <- max(cytosolmask)
+
+      # Go through every stained cytosol and check for nucleus
+      for(j in 1:no_of_cytosols){
+        collocation_found <- max((cytosolmask==j)*nmask)
+        if(collocation_found == 0){
+          cytosolmask[cytosolmask==j] <- 0
+        }
+        rm(j)
+      }
+
+      cytosolmask <- EBImage::bwlabel(cytosolmask)
+      no_of_cytosols <- max(cytosolmask)
+
+      # Combine nmask and cytosolmask and count the resulting cell bodies
+      # (nuclei that are within the stained proteins in the cytosol)
+      n_c_mask <- nmask_watershed*(!cytosolmask==0)
+      #display(n_c_mask)
+
+      table_n_c_mask <- table(n_c_mask)
+
+      # Count number of cells containing staining for protein
+      cell_with_proteins_No <- length(names(table_n_c_mask))-1
+      #display(n_c_mask)
+
+
+      # remove objects that are smaller than min_nuc_size
+      to_be_removed <- as.integer(names(which(table_n_c_mask < nuc_min_size)))
+      if(length(to_be_removed) > 0){
+        for(j in 1:length(to_be_removed)){
+          EBImage::imageData(n_c_mask)[
+            EBImage::imageData(n_c_mask) == to_be_removed[j]] <- 0
+        }
+        rm(j)
+      }
+
+      # Add border of cytosols with proteins and save file
+      Image_cytosol_numbers_proteins <- Image_nuclei_numbers
+      EBImage::colorMode(Image_cytosol_numbers_proteins) <- "color"
+
+      Image_cytosol_numbers_proteins <- EBImage::paintObjects(
+        x = cytosolmask,
+        tgt = Image_cytosol_numbers_proteins,
+        opac = c(1),
+        col=c('#FFFF00'))
+
+      #display(Image_cytosol_numbers_proteins)
+
+      # Display the number of cells with proteins
+      print(paste("Number of cells that contain other colored proteins: ",
+                  cell_with_proteins_No, sep=""))
+
+    }
+
 
 
     # -------------------------------------------------------------------- #
@@ -522,10 +622,15 @@ cellPixels <- function(input_dir = NULL,
     df_results[i,"dimension_y"] <- dim(image_loaded)[1]
     df_results[i,"number_of_nuclei"] <- nucNo
     if(!is.null(protein_in_nuc_color) & protein_in_nuc_color != "none"){
-      df_results[i,"color_of_second_proteins_in_nuclei"] <- protein_in_nuc_color
+      df_results[i,"color_of_second_protein_in_nuclei"] <- protein_in_nuc_color
       df_results[i,"number_of_nuclei_with_second_protein"] <- nuc_with_proteins_No
     }
 
+    if(!is.null(protein_in_cytosol_color) & protein_in_cytosol_color != "none"){
+      "color_of_third_protein_in_cytosol" <- protein_in_cytosol_color
+      "number_of_cells_with_third_protein" <- cell_with_proteins_No
+    }
+
     df_results[i,"intensity_sum_red_full"] <- sum(image_loaded[,,1])
     df_results[i,"intensity_sum_green_full"] <- sum(image_loaded[,,2])
     df_results[i,"intensity_sum_blue_full"] <- sum(image_loaded[,,3])
@@ -598,7 +703,19 @@ cellPixels <- function(input_dir = NULL,
       tiff::writeTIFF(what = Image_nuclei_numbers_proteins,
                       where = paste(output_dir,
                                     image_name_wo_czi,
-                                    "_nuclei_numbers_proteins.tif",
+                                    "_nuclei_numbers_proteins1_nuc.tif",
+                                    sep = ""),
+                      bits.per.sample = 8L, compression = "none",
+                      reduce = TRUE)
+    }
+
+    # Images with marked nuclei and borders around the third protein in
+    # cell bodies (proteins in cytosol)
+    if(!is.null(protein_in_cytosol_color) & protein_in_cytosol_color != "none"){
+      tiff::writeTIFF(what = Image_cytosol_numbers_proteins,
+                      where = paste(output_dir,
+                                    image_name_wo_czi,
+                                    "_nuclei_numbers_proteins2_cell.tif",
                                     sep = ""),
                       bits.per.sample = 8L, compression = "none",
                       reduce = TRUE)
@@ -629,7 +746,9 @@ cellPixels <- function(input_dir = NULL,
                         "nucleus_color","number_of_czis",
                         "number_of_pixels_at_border_to_disregard",
                         "number_size_factor", "output_dir",
-                        "protein_in_nuc_color", ".old.options")
+                        "protein_in_cytosol_color",
+                        "protein_in_nuc_color",
+                        ".old.options")
 
     remove_variables <- list_of_variables[
       !(list_of_variables %in% keep_variables)]

diff --git a/README.md b/README.md
@@ -5,6 +5,7 @@ The package need at least R 4.0.0.
 It uses the R packages "reticulate" to load and use python packages (this will install miniconda when first used),
 "EBImage" for finding nuclei and contrast enhancement as well as "tiff" for saving the results in the tif format.
 We are using the python package "czifile" to directly work with the microscopy image format czi.
+Important: Because this pacakge makes use of a python package which is being installed on-the-fly, you need internet connection.
 
 
 ## Code for using the R package

diff --git a/inst/testscriptDevelop.R b/inst/testscriptDevelop.R
@@ -7,6 +7,8 @@
 #   Test Package:              'Ctrl + Shift + T'
 
 
+# TODO: Im Namen sollte ersichtlich sein, welche Farbe gesucht und markiert wurde.
+
 # Delete everything in the environment
 rm(list = ls())
 # close all open plots in RStudio
@@ -16,7 +18,7 @@ graphics.off()
 # >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
 
 # Directory of the images
-input_dir <- "test3/"
+input_dir <- "test4/"
 
 # <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
 
@@ -38,7 +40,7 @@ require(devtools)
 require(reticulate)
 
 # Check package
-check()
+#check()
 
 # Document package
 document()
@@ -50,7 +52,8 @@ load_all()
 
 df_results <- cellPixels(input_dir = input_dir,
                          nucleus_color = "blue",
-                         protein_in_nuc_color = "none",
+                         protein_in_nuc_color = "red",
+                         protein_in_cytosol_color = "green",
                          number_size_factor = 0.2)
 
 save(df_results, file=paste(input_dir, "output/df_results.Rda", sep=""))
diff --git a/man/cellPixels.Rd b/man/cellPixels.Rd