Add Plate 3 and run IC pipeline

.gitignore

@@ -1,14 +1,18 @@
 # ignore all plates as they are downloaded from figshare in instructions
 0.download_data/Plate_1
 0.download_data/Plate_2
+0.download_data/Plate_3
 
 # ignore pycache
 __pycache__
 
-# ignore corrected plates images (like in download data
+# ignore corrected plates images (like in download data)
 1.cellprofiler_ic/Corrected_Plate_1
 1.cellprofiler_ic/Corrected_Plate_2
+1.cellprofiler_ic/Corrected_Plate_3
 
 # ignore log files
 *logs
 
+# ignore Mac related files
+.DS_Store

0.download_data/download_plates.ipynb

@@ -24,7 +24,9 @@
    "source": [
     "import pathlib\n",
     "\n",
-    "from utils.download_figshare import download_figshare"
+    "import sys\n",
+    "sys.path.append(\"../\")\n",
+    "from utils import download_figshare as downfig"
    ]
   },
   {
@@ -56,7 +58,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Set dictionary with specific path/variables for each plate"
+    "## Set dictionary with specific path/variables for each plate\n",
+    "\n",
+    "**Note:** You are able to see the correct URL for the plate by copying the link from the `Download all` button on the item (term used for dataset/plate) from the NF1 Schwann Cell Genotype Cell Painting Assay project. As well, there are mutliple versions of this dataset due to correcting the number of images and the metadata files."
    ]
   },
   {
@@ -65,17 +69,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# since we are dealing with zip files, we use the optional parameter `output_dir` where we specify where to extact the files to\n",
+    "# since we are dealing with zip files, we use the optional parameter `output_dir` where we \n",
+    "# specify where to extact the files to\n",
     "download_plates_info_dictionary = {\n",
     "    \"Plate_1\": {\n",
     "        \"figshare_id\": \"22233292\",\n",
-    "        \"version_number\": \"1\",\n",
+    "        \"version_number\": \"2\",\n",
     "        \"output_folder\": \"Plate_1_zip\",\n",
     "        \"output_dir\": pathlib.Path(\"Plate_1\"),\n",
     "    },\n",
     "    \"Plate_2\": {\n",
     "        \"figshare_id\": \"22233700\",\n",
-    "        \"version_number\": \"3\",\n",
+    "        \"version_number\": \"4\",\n",
     "        \"output_folder\": \"Plate_2_zip\",\n",
     "        \"output_dir\": pathlib.Path(\"Plate_2\"),\n",
     "    },\n",
@@ -118,7 +123,7 @@
     "    output_dir = plate_info[\"output_dir\"]\n",
     "\n",
     "    # download images and metadata for both plates\n",
-    "    download_figshare(\n",
+    "    downfig.download_figshare(\n",
     "        figshare_id=figshare_id,\n",
     "        output_file=output_folder,\n",
     "        output_dir=output_dir,\n",

0.download_data/metadata/barcode_platemap.csv

@@ -1,2 +1,4 @@
-Assay_Plate_Barcode,Plate_Map_Name
-1,platemap_NF1_CP
+Assay_Plate_Barcode,Plate_Map_Name
+plate_1,platemap_NF1_plate1
+plate_2,platemap_NF1_plate2
+plate_3,platemap_NF1_plate3

0.download_data/metadata/platemap_NF1_plate3.csv

@@ -0,0 +1,73 @@
+WellRow,WellCol,well_position,gene_name,genotype,seed_density
+B,1,B01,NF1,WT,500
+C,1,C01,NF1,WT,500
+D,1,D01,NF1,WT,500
+E,1,E01,NF1,WT,500
+F,1,F01,NF1,WT,500
+G,1,G01,NF1,WT,500
+B,2,B02,NF1,WT,1000
+C,2,C02,NF1,WT,1000
+D,2,D02,NF1,WT,1000
+E,2,E02,NF1,WT,1000
+F,2,F02,NF1,WT,1000
+G,2,G02,NF1,WT,1000
+B,3,B03,NF1,WT,2000
+C,3,C03,NF1,WT,2000
+D,3,D03,NF1,WT,2000
+E,3,E03,NF1,WT,2000
+F,3,F03,NF1,WT,2000
+G,3,G03,NF1,WT,2000
+B,4,B04,NF1,WT,4000
+C,4,C04,NF1,WT,4000
+D,4,D04,NF1,WT,4000
+E,4,E04,NF1,WT,4000
+F,4,F04,NF1,WT,4000
+G,4,G4,NF1,WT,4000
+B,5,B05,NF1,HET,500
+C,5,C05,NF1,HET,500
+D,5,D05,NF1,HET,500
+E,5,E05,NF1,HET,500
+F,5,F05,NF1,HET,500
+G,5,G05,NF1,HET,500
+B,6,B06,NF1,HET,1000
+C,6,C06,NF1,HET,1000
+D,6,D06,NF1,HET,1000
+E,6,E06,NF1,HET,1000
+F,6,F06,NF1,HET,1000
+G,6,G06,NF1,HET,1000
+B,7,B07,NF1,HET,2000
+C,7,C07,NF1,HET,2000
+D,7,D07,NF1,HET,2000
+E,7,E07,NF1,HET,2000
+F,7,F07,NF1,HET,2000
+G,7,G07,NF1,HET,2000
+B,8,B08,NF1,HET,4000
+C,8,C08,NF1,HET,4000
+D,8,D08,NF1,HET,4000
+E,8,E08,NF1,HET,4000
+F,8,F08,NF1,HET,4000
+G,8,G08,NF1,HET,4000
+B,9,B09,NF1,NULL,500
+C,9,C09,NF1,NULL,500
+D,9,D09,NF1,NULL,500
+E,9,E09,NF1,NULL,500
+F,9,F09,NF1,NULL,500
+G,9,G09,NF1,NULL,500
+B,10,B10,NF1,NULL,1000
+C,10,C10,NF1,NULL,1000
+D,10,D10,NF1,NULL,1000
+E,10,E10,NF1,NULL,1000
+F,10,F10,NF1,NULL,1000
+G,10,G10,NF1,NULL,1000
+B,11,B11,NF1,NULL,2000
+C,11,C11,NF1,NULL,2000
+D,11,D11,NF1,NULL,2000
+E,11,E11,NF1,NULL,2000
+F,11,F11,NF1,NULL,2000
+G,11,G11,NF1,NULL,2000
+B,12,B12,NF1,NULL,4000
+C,12,C12,NF1,NULL,4000
+D,12,D12,NF1,NULL,4000
+E,12,E12,NF1,NULL,4000
+F,12,F12,NF1,NULL,4000
+G,12,G12,NF1,NULL,4000

0.download_data/scripts/download_plates.py

@@ -9,7 +9,10 @@
 
 
 import pathlib
-from utils.download_figshare import download_figshare
+
+import sys
+sys.path.append("../")
+from utils import download_figshare as downfig
 
 
 # ## Set constant paths/variables
@@ -28,20 +31,24 @@
 
 
 # ## Set dictionary with specific path/variables for each plate
+# 
+# **Note:** You are able to see the correct URL for the plate by copying the link from the `Download all` button on the item (term used for dataset/plate) from the NF1 Schwann Cell Genotype Cell Painting Assay project. As well, there are mutliple versions of this dataset due to correcting the number of images and the metadata files.
 
 # In[3]:
 
 
+# since we are dealing with zip files, we use the optional parameter `output_dir` where we 
+# specify where to extact the files to
 download_plates_info_dictionary = {
     "Plate_1": {
         "figshare_id": "22233292",
-        "version_number": "1",
+        "version_number": "2",
         "output_folder": "Plate_1_zip",
         "output_dir": pathlib.Path("Plate_1"),
     },
     "Plate_2": {
         "figshare_id": "22233700",
-        "version_number": "3",
+        "version_number": "4",
         "output_folder": "Plate_2_zip",
         "output_dir": pathlib.Path("Plate_2"),
     },
@@ -54,19 +61,22 @@
 
 
 for plate in download_plates_info_dictionary:
-    # Access the plate info stored in the dictionary
+    # access the plate info stored in the dictionary
     plate_info = download_plates_info_dictionary[plate]
+    # set the parameters for the function as variables based on the plate dictionary info
     figshare_id = str(
         plate_info["figshare_id"] + "/versions/" + plate_info["version_number"]
     )
     output_folder = plate_info["output_folder"]
     output_dir = plate_info["output_dir"]
 
-    download_figshare(
+    # download images and metadata for both plates
+    downfig.download_figshare(
         figshare_id=figshare_id,
         output_file=output_folder,
         output_dir=output_dir,
         metadata_dir=metadata_dir,
         figshare_url=figshare_url,
         unzip_files=unzip_files,
     )
+