From 85611fc0cca60634f88dd60d4d4781c3ad95d789 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Tue, 11 Apr 2023 15:03:30 -0600 Subject: [PATCH 01/15] Edit main README and correct metadata files --- 0.download_data/metadata/barcode_platemap.csv | 6 +- .../metadata/barcode_platemap_Plate2.csv | 2 - ...map_NF1_CP.csv => platemap_NF1_plate1.csv} | 0 ..._CP_Plate2.csv => platemap_NF1_plate2.csv} | 0 .../metadata/platemap_NF1_plate3.csv | 55 ++++++++++++++++++ README.md | 32 +++++++++- .../Modified_CellPainting_Plate3.png | Bin 0 -> 1054916 bytes example_figures/plate1_nf1_platemap.png | Bin 0 -> 377202 bytes example_figures/plate2_nf1_platemap.png | Bin 0 -> 473743 bytes example_figures/plate3_nf1_platemap.png | Bin 0 -> 572279 bytes 10 files changed, 90 insertions(+), 5 deletions(-) delete mode 100644 0.download_data/metadata/barcode_platemap_Plate2.csv rename 0.download_data/metadata/{platemap_NF1_CP.csv => platemap_NF1_plate1.csv} (100%) rename 0.download_data/metadata/{platemap_NF1_CP_Plate2.csv => platemap_NF1_plate2.csv} (100%) create mode 100644 0.download_data/metadata/platemap_NF1_plate3.csv create mode 100644 example_figures/Modified_CellPainting_Plate3.png create mode 100644 example_figures/plate1_nf1_platemap.png create mode 100644 example_figures/plate2_nf1_platemap.png create mode 100644 example_figures/plate3_nf1_platemap.png diff --git a/0.download_data/metadata/barcode_platemap.csv b/0.download_data/metadata/barcode_platemap.csv index 208d69e..e210270 100644 --- a/0.download_data/metadata/barcode_platemap.csv +++ b/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 \ No newline at end of file diff --git a/0.download_data/metadata/barcode_platemap_Plate2.csv b/0.download_data/metadata/barcode_platemap_Plate2.csv deleted file mode 100644 index 55ca4e0..0000000 --- a/0.download_data/metadata/barcode_platemap_Plate2.csv +++ /dev/null @@ -1,2 +0,0 @@ -Assay_Plate_Barcode,Plate_Map_Name -2,platemap_NF1_CP_Plate2 diff --git a/0.download_data/metadata/platemap_NF1_CP.csv b/0.download_data/metadata/platemap_NF1_plate1.csv similarity index 100% rename from 0.download_data/metadata/platemap_NF1_CP.csv rename to 0.download_data/metadata/platemap_NF1_plate1.csv diff --git a/0.download_data/metadata/platemap_NF1_CP_Plate2.csv b/0.download_data/metadata/platemap_NF1_plate2.csv similarity index 100% rename from 0.download_data/metadata/platemap_NF1_CP_Plate2.csv rename to 0.download_data/metadata/platemap_NF1_plate2.csv diff --git a/0.download_data/metadata/platemap_NF1_plate3.csv b/0.download_data/metadata/platemap_NF1_plate3.csv new file mode 100644 index 0000000..ac9b5fc --- /dev/null +++ b/0.download_data/metadata/platemap_NF1_plate3.csv @@ -0,0 +1,55 @@ +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,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,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 \ No newline at end of file diff --git a/README.md b/README.md index 63880e5..778647f 100644 --- a/README.md +++ b/README.md @@ -3,6 +3,7 @@ ## Data The data we use is a modified Cell Painting assay on [Schwann cells](https://www.ncbi.nlm.nih.gov/books/NBK544316/) from patients with [Neurofibromatosis type 1 (NF1)](https://medlineplus.gov/genetics/condition/neurofibromatosis-type-1/). + In this modified Cell Painting, there are three channels for plates 1 and 2: - `DAPI` (Nuclei) @@ -11,6 +12,15 @@ In this modified Cell Painting, there are three channels for plates 1 and 2: ![Modified_Cell_Painting.png](example_figures/Modified_Cell_Painting.png) +In this modified Cell Painting, there are four channels for plates 3 and 3': + +- `DAPI` (Nuclei) +- `GFP` (Endoplasmic Reticulum) +- `CY5` (Mitochondria) +- `RFP` (Actin) + +![Modified_CellPainting_Plate3.png](example_figures/Modified_CellPainting_Plate3.png) + Plates 1 and 2 measure Cell Painting in isogenic Schwann cells with two different NF1 genotypes: **Plate 1** @@ -18,11 +28,30 @@ Plates 1 and 2 measure Cell Painting in isogenic Schwann cells with two differen - Null (`Null -/-`): In column 7 from the plate (e.g C7, D7, etc.) There are only rows C-F in this plate. +![plate1_nf1_platemap.png](example_figures/plate1_nf1_platemap.png) + **Plate 2** - Wild type (`WT +/+`): Columns 1 and 6 - Null (`Null -/-`): Columns 7 and 12 This plate uses all rows (e.g., A-H) +![plate2_nf1_platemap.png](example_figures/plate2_nf1_platemap.png) + +Plates 3 and 3' measure Cell Painting in isogenic Schwann cells with all three different NF1 genotypes: + +**Plate 3 and 3'** +For these plates, we looking at different seeding densities to identify which will lower the cell count contribution on the features and identify differential features between genotypes. +As well, the plates have different culturing conditions, where plate 3 cells were cultured in 10% FBS versus plate 3' culturing in 5% FBS. +- Wild type (`WT +/+`): Columns 1-3 +- Heterzygous (`HET +/-`): Columns 5-7 +- Null (`Null -/-`): Columns 9-11 +- Seeding density: + - 500 -> Columns 1, 5, and 9 + - 1000 -> Columns 2, 6, and 10 + - 2000 -> Columns 3, 7, and 11 + +![plate3_nf1_platemap.png](example_figures/plate3_nf1_platemap.png) + It is important to study Schwann cells from NF1 patients because NF1 causes patients to develop neurofibromas, which are red bumps on the skin (tumors) that appear due to the loss of Ras-GAP neurofibromin. This loss occurs when the NF1 gene is mutated (NF1 +/-). @@ -37,8 +66,9 @@ Once we discover a biomarker from these cells, we hope that our method can be us | Module | Purpose | Description | | :---- | :----- | :---------- | -| [0.download_data](0.download_data/) | Download NF1 pilot data | Download images from each plate of NF1 dataset for analysis from Figshare | +| [0.download_data](0.download_data/) | Download NF1 data | Download images from each plate of the NF1 dataset for analysis from Figshare | | [1.cellprofiler_ic](1.cellprofiler_ic/) | Apply CellProfiler illumination correction (IC)| Use a CellProfiler pipeline to calculate and apply IC the images and save them | +| [2.cellprofiler_analysis](2.cellprofiler_analysis/) | Perform CellProfiler analysis on corrected images | Use a CellProfiler pipeline to segment single cells and extract features into a SQLite file | ## Main environment diff --git a/example_figures/Modified_CellPainting_Plate3.png 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zc4)J1D@w9{bb%l~cTC>~@GlP0ONu=^R|Yhp$$V)D`qGKUX79yGu~!7(c9HS=|1fQ3u1;)6Xe>+<<*WTB0Ung&6gf1o%CSv6lPk>P{u zMY^M0X8}Jl?7Ff{r=>M))NO@8&YO+UJ<5ceh={^*KXX48i;w8nE|h?li|h@@VS(46 zb721|aT)9BLn}O*1UE%0YUrlroggERenc@GCp4XVcrEMe zYrv39f?V75t;l8(sc}|b5W6xS6ko2md%4cSmCG2Jd_V1#>Q6t|jPm)LXSwpmYW~tr zIhE31mRm&kWQ!9ho|lvIsgyCzwY1#ym{9*~#jC+od+v_WJx&kUpi8gw-?%};iahXA zdd!Cr){zz(T3@tdm}c)CqvJlJfVbRSqA4D?kc#8A`Ro8*QJ*iR`g$mQ4?nmzkLDYl z9o%-%Cs1L`Z&Eio^G4Q(N45-yuQ|qR?p2k6--Pv+Qv8CeAmTF2j3$8vx-y&Wfa+lnhUt+VXmGC$5?Ln@JR0 zQ@E;sOSmV;#DCp`AUp$=0hpMl{^`GPf>jBS*X+i@lpjsH4P2aR2Y~I*O_|Y?<(Njq zKmX-Nh9EpO{QF6?xJF5R_$dV8rxH$GF;!M6JUA%fr1M@=&1la72*SO{^(KSxtuWvB z&hr3d;s0)8(|$wR2{&w>_BFbiDr?Sm2*PXWJ4^=Q#~}#cvUSU=uD-v}lqntqbR+>; zx0c!gJ}T3+V7W5{;di!6j2~>=C{fTTSF|lP*(iU8m9f6z-VaQb_5YYrk`Q5@W7CWo zGZw$AkS}uB{fp(tF4Il^Q;YWo`r^Mc*)fpMoYgk8rkiS{i=Cf6yK!UtW)l_Sow0W| zmmm?jCTo)U@uu>fRp!G{%&z4xT+646k{8 Date: Wed, 12 Apr 2023 08:40:32 -0600 Subject: [PATCH 02/15] add 4000 seeding density to metadata plate 3 --- .../metadata/platemap_NF1_plate3.csv | 20 ++++++++++++++++++- 1 file changed, 19 insertions(+), 1 deletion(-) diff --git a/0.download_data/metadata/platemap_NF1_plate3.csv b/0.download_data/metadata/platemap_NF1_plate3.csv index ac9b5fc..0ab91cd 100644 --- a/0.download_data/metadata/platemap_NF1_plate3.csv +++ b/0.download_data/metadata/platemap_NF1_plate3.csv @@ -17,6 +17,12 @@ 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 @@ -35,6 +41,12 @@ 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 @@ -52,4 +64,10 @@ 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 \ No newline at end of file +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 \ No newline at end of file From f61eafee0425001a702f430f3c156881e62c1769 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 08:45:51 -0600 Subject: [PATCH 03/15] correct plate 3 documentation and plate map --- README.md | 1 + example_figures/plate3_nf1_platemap.png | Bin 572279 -> 620642 bytes 2 files changed, 1 insertion(+) diff --git a/README.md b/README.md index 778647f..545c870 100644 --- a/README.md +++ b/README.md @@ -49,6 +49,7 @@ As well, the plates have different culturing conditions, where plate 3 cells wer - 500 -> Columns 1, 5, and 9 - 1000 -> Columns 2, 6, and 10 - 2000 -> Columns 3, 7, and 11 + - 4000 -> Columns 4, 8, and 12 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zx0c!gJ}T3+V7W5{;di!6j2~>=C{fTTSF|lP*(iU8m9f6z-VaQb_5YYrk`Q5@W7CWo zGZw$AkS}uB{fp(tF4Il^Q;YWo`r^Mc*)fpMoYgk8rkiS{i=Cf6yK!UtW)l_Sow0W| zmmm?jCTo)U@uu>fRp!G{%&z4xT+646k{8 Date: Wed, 12 Apr 2023 08:46:28 -0600 Subject: [PATCH 04/15] edit gitignore to ignore images from plate 3 and mac files --- .gitignore | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 8aef57d..2e514f2 100644 --- a/.gitignore +++ b/.gitignore @@ -1,14 +1,17 @@ # 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 # ignore log files *logs +# ignore Mac related files +.DS_Store From 985a2d04420bc724db8de179838bcab3065c7d5e Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 13:18:38 -0600 Subject: [PATCH 05/15] make bold that env must be activated before runs --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 545c870..27da6fb 100644 --- a/README.md +++ b/README.md @@ -82,7 +82,7 @@ To create the environment, run the below code block: conda env create -f nf1_cellpainting_env.yml ``` -Make sure that the conda environment is activated before running notebooks or scripts: +**Make sure that the conda environment is activated before running notebooks or scripts:** ```bash conda activate nf1_cellpainting_data From 251faeb9f9cd11f72215983806321e1a38a0338b Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 14:16:22 -0600 Subject: [PATCH 06/15] rerun download plates --- 0.download_data/download_plates.ipynb | 17 +++++++++++------ 0.download_data/scripts/download_plates.py | 20 +++++++++++++++----- 2 files changed, 26 insertions(+), 11 deletions(-) diff --git a/0.download_data/download_plates.ipynb b/0.download_data/download_plates.ipynb index acf85b2..df4e168 100644 --- a/0.download_data/download_plates.ipynb +++ b/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", diff --git a/0.download_data/scripts/download_plates.py b/0.download_data/scripts/download_plates.py index 7e61134..b4d52a6 100644 --- a/0.download_data/scripts/download_plates.py +++ b/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"), }, @@ -54,15 +61,17 @@ 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, @@ -70,3 +79,4 @@ figshare_url=figshare_url, unzip_files=unzip_files, ) + From aea50bebe771859d01ab54f0b02b580c3231df3d Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 14:41:11 -0600 Subject: [PATCH 07/15] update cp utils file --- utils/cp_utils.py | 37 ++++++++++++++++++++++++++++++------- 1 file changed, 30 insertions(+), 7 deletions(-) diff --git a/utils/cp_utils.py b/utils/cp_utils.py index dae7ef8..d0eec46 100644 --- a/utils/cp_utils.py +++ b/utils/cp_utils.py @@ -60,14 +60,19 @@ def run_cellprofiler( multiple sets of images (e.g., per plate) so that the outputs will have different names (default is None) analysis_run (bool, optional): will use functions to complete an analysis pipeline (default is False) """ - # check to make sure all paths are correct and the directory exists before + # check to make sure paths to pipeline and images are correct before running the pipeline if not os.path.exists(path_to_pipeline): raise FileNotFoundError(f"Directory '{path_to_pipeline}' does not exist") - if not os.path.exists(path_to_output): - raise FileNotFoundError(f"Directory '{path_to_output}' does not exist") if not os.path.exists(path_to_images): raise FileNotFoundError(f"Directory '{path_to_images}' does not exist") + # make logs directory + log_dir = pathlib.Path("./logs") + os.makedirs(log_dir, exist_ok=True) + + # make output directory if it is not already created + os.makedirs(path_to_output, exist_ok=True) + # run CellProfiler illumination correction pipeline if not analysis_run: print(f"Starting CellProfiler run on {pathlib.Path(path_to_images).name}") @@ -90,12 +95,22 @@ def run_cellprofiler( "-i", path_to_images, ] - subprocess.run(command, capture_output=cellprofiler_output_file, check=True) + subprocess.run( + command, + stdout=cellprofiler_output_file, + stderr=cellprofiler_output_file, + check=True, + ) + print( + f"The CellProfiler run has been completed with {pathlib.Path(path_to_images).name}. Please check log file for any errors." + ) # run CellProfiler analysis pipeline if analysis_run: - if sqlite_name is None: - raise ValueError("You have not set a name for the SQLite file. Please add a sqlite_name for the analysis output.") + if sqlite_name is None: + raise ValueError( + "You have not set a name for the SQLite file. Please add a sqlite_name for the analysis output." + ) # runs through any files that are in the output path if any( files.name.startswith(sqlite_name) @@ -121,7 +136,15 @@ def run_cellprofiler( "-i", path_to_images, ] - subprocess.run(command, capture_output=cellprofiler_output_file, check=True) + subprocess.run( + command, + stdout=cellprofiler_output_file, + stderr=cellprofiler_output_file, + check=True, + ) + print( + f"The CellProfiler run has been completed with {pathlib.Path(path_to_images).name}. Please check log file for any errors." + ) if sqlite_name: # rename the outputted .sqlite file as a specified name (used when running multiple plates with same CP pipeline) From 3ec8394a0a28120ac0b00b0cc875b7544c06f582 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 14:45:19 -0600 Subject: [PATCH 08/15] edit main env to be usable on Mac --- nf1_cellpainting_env.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/nf1_cellpainting_env.yml b/nf1_cellpainting_env.yml index 361a3cc..52f704d 100644 --- a/nf1_cellpainting_env.yml +++ b/nf1_cellpainting_env.yml @@ -12,7 +12,8 @@ dependencies: - conda-forge::numpy - conda-forge::matplotlib - conda-forge::pandas -- conda-forge::mysqlclient +# this package must be hardcoded to work with Mac +- conda-forge::mysqlclient=1.4.6 - conda-forge::openjdk - conda-forge::scikit-learn - conda-forge::mahotas From d260d7502e8b0bb1634f1e84c4904812f5044529 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 15:03:30 -0600 Subject: [PATCH 09/15] run notebook (not to finish) and add new pipeline for plate 3 --- 1.cellprofiler_ic/NF1_illum_Plate3.cppipe | 272 ++++++++++++++++++ ...lum.cppipe => NF1_illum_Plates_1_2.cppipe} | 0 1.cellprofiler_ic/nf1_ic.ipynb | 47 ++- 3 files changed, 311 insertions(+), 8 deletions(-) create mode 100644 1.cellprofiler_ic/NF1_illum_Plate3.cppipe rename 1.cellprofiler_ic/{NF1_illum.cppipe => NF1_illum_Plates_1_2.cppipe} (100%) diff --git a/1.cellprofiler_ic/NF1_illum_Plate3.cppipe b/1.cellprofiler_ic/NF1_illum_Plate3.cppipe new file mode 100644 index 0000000..4b46540 --- /dev/null +++ b/1.cellprofiler_ic/NF1_illum_Plate3.cppipe @@ -0,0 +1,272 @@ +CellProfiler Pipeline: http://www.cellprofiler.org +Version:5 +DateRevision:424 +GitHash: +ModuleCount:13 +HasImagePlaneDetails:False + +Images:[module_num:1|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['To begin creating your project, use the Images module to compile a list of files and/or folders that you want to analyze. You can also specify a set of rules to include only the desired files in your selected folders.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + : + Filter images?:Images only + Select the rule criteria:and (extension does isimage) (directory doesnot containregexp "[\\\\/]\\.") + +Metadata:[module_num:2|svn_version:'Unknown'|variable_revision_number:6|show_window:False|notes:['The Metadata module optionally allows you to extract information describing your images (i.e, metadata) which will be stored along with your measurements. This information can be contained in the file name and/or location, or in an external file.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Extract metadata?:No + Metadata data type:Text + Metadata types:{} + Extraction method count:1 + Metadata extraction method:Extract from file/folder names + Metadata source:File name + Regular expression to extract from file name:^(?P.*)_(?P[A-P][0-9]{2})_s(?P[0-9])_w(?P[0-9]) + Regular expression to extract from folder name:(?P[0-9]{4}_[0-9]{2}_[0-9]{2})$ + Extract metadata from:All images + Select the filtering criteria:and (file does contain "") + Metadata file location:Elsewhere...| + Match file and image metadata:[] + Use case insensitive matching?:No + Metadata file name:None + Does cached metadata exist?:No + +NamesAndTypes:[module_num:3|svn_version:'Unknown'|variable_revision_number:8|show_window:False|notes:['The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Assign a name to:Images matching rules + Select the image type:Grayscale image + Name to assign these images:DNA + Match metadata:[] + Image set matching method:Order + Set intensity range from:Image metadata + Assignments count:4 + Single images count:0 + Maximum intensity:255.0 + Process as 3D?:No + Relative pixel spacing in X:1.0 + Relative pixel spacing in Y:1.0 + Relative pixel spacing in Z:1.0 + Select the rule criteria:and (file does contain "DAPI") + Name to assign these images:OrigDAPI + Name to assign these objects:Cell + Select the image type:Grayscale image + Set intensity range from:Image metadata + Maximum intensity:255.0 + Select the rule criteria:and (file does contain "GFP") + Name to assign these images:OrigGFP + Name to assign these objects:Nucleus + Select the image type:Grayscale image + Set intensity range from:Image metadata + Maximum intensity:255.0 + Select the rule criteria:and (file does contain "RFP") + Name to assign these images:OrigRFP + Name to assign these objects:Cytoplasm + Select the image type:Grayscale image + Set intensity range from:Image metadata + Maximum intensity:255.0 + Select the rule criteria:and (file does contain "CY5") + Name to assign these images:OrigMito + Name to assign these objects:Speckle + Select the image type:Grayscale image + Set intensity range from:Image metadata + Maximum intensity:255.0 + +Groups:[module_num:4|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['The Groups module optionally allows you to split your list of images into image subsets (groups) which will be processed independently of each other. Examples of groupings include screening batches, microtiter plates, time-lapse movies, etc.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Do you want to group your images?:No + grouping metadata count:1 + Metadata category:None + +CorrectIlluminationCalculate:[module_num:5|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Since for all seeding densities, Schwann cells do not take up a ton of space in the images, we use Background in the IC calculations.', '', 'Block size 50 seems to work best for the DAPI channel (nuclei), as well as using the Fit Polynomial smoothing method as it seemed to not over correct as compared to the other methods.', '', 'We use the each method for calculating IC functions as this seemed to produce the best results over creating one from all images in a channel.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the input image:OrigDAPI + Name the output image:IllumDAPI + Select how the illumination function is calculated:Background + Dilate objects in the final averaged image?:No + Dilation radius:1 + Block size:50 + Rescale the illumination function?:No + Calculate function for each image individually, or based on all images?:Each + Smoothing method:Fit Polynomial + Method to calculate smoothing filter size:Automatic + Approximate object diameter:80 + Smoothing filter size:200 + Retain the averaged image?:No + Name the averaged image:IllumBlueAvg + Retain the dilated image?:No + Name the dilated image:IllumBlueDilated + Automatically calculate spline parameters?:No + Background mode:dark + Number of spline points:5 + Background threshold:2.0 + Image resampling factor:2.0 + Maximum number of iterations:40 + Residual value for convergence:0.001 + +CorrectIlluminationCalculate:[module_num:6|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Since for all seeding densities, Schwann cells do not take up a ton of space in the images, we use Background in the IC calculations.', '', 'Block size 50 seems to work best for the GFP channel (ER), as well as using the Fit Polynomial smoothing method as it seemed to not over correct as compared to the other methods.', '', 'We use the each method for calculating IC functions as this seemed to produce the best results over creating one from all images in a channel.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the input image:OrigGFP + Name the output image:IllumGFP + Select how the illumination function is calculated:Background + Dilate objects in the final averaged image?:No + Dilation radius:1 + Block size:50 + Rescale the illumination function?:No + Calculate function for each image individually, or based on all images?:Each + Smoothing method:Fit Polynomial + Method to calculate smoothing filter size:Automatic + Approximate object diameter:200 + Smoothing filter size:200 + Retain the averaged image?:No + Name the averaged image:IllumBlueAvg + Retain the dilated image?:No + Name the dilated image:IllumBlueDilated + Automatically calculate spline parameters?:Yes + Background mode:auto + Number of spline points:5 + Background threshold:2.0 + Image resampling factor:2.0 + Maximum number of iterations:40 + Residual value for convergence:0.001 + +CorrectIlluminationCalculate:[module_num:7|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Since for all seeding densities, Schwann cells do not take up a ton of space in the images, we use Background in the IC calculations.', '', 'Block size 15 seems to work best for the RFP channel (actin), as well as using the Fit Polynomial smoothing method as it seemed to not over correct as compared to the other methods.', '', 'We use the each method for calculating IC functions as this seemed to produce the best results over creating one from all images in a channel.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the input image:OrigRFP + Name the output image:IllumRFP + Select how the illumination function is calculated:Background + Dilate objects in the final averaged image?:No + Dilation radius:1 + Block size:15 + Rescale the illumination function?:No + Calculate function for each image individually, or based on all images?:Each + Smoothing method:Fit Polynomial + Method to calculate smoothing filter size:Automatic + Approximate object diameter:10 + Smoothing filter size:600 + Retain the averaged image?:No + Name the averaged image:IllumBlueAvg + Retain the dilated image?:No + Name the dilated image:IllumBlueDilated + Automatically calculate spline parameters?:Yes + Background mode:auto + Number of spline points:5 + Background threshold:2.0 + Image resampling factor:2.0 + Maximum number of iterations:40 + Residual value for convergence:0.001 + +CorrectIlluminationCalculate:[module_num:8|svn_version:'Unknown'|variable_revision_number:2|show_window:False|notes:['Since for all seeding densities, Schwann cells do not take up a ton of space in the images, we use Background in the IC calculations.', '', 'Block size 15 seems to work best for the CY5 channel (mitochondria), as well as using the Fit Polynomial smoothing method as it seemed to not over correct as compared to the other methods.', '', 'We use the each method for calculating IC functions as this seemed to produce the best results over creating one from all images in a channel.']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the input image:OrigMito + Name the output image:IllumMito + Select how the illumination function is calculated:Background + Dilate objects in the final averaged image?:No + Dilation radius:1 + Block size:15 + Rescale the illumination function?:No + Calculate function for each image individually, or based on all images?:Each + Smoothing method:Fit Polynomial + Method to calculate smoothing filter size:Automatic + Approximate object diameter:10 + Smoothing filter size:600 + Retain the averaged image?:No + Name the averaged image:IllumBlueAvg + Retain the dilated image?:No + Name the dilated image:IllumBlueDilated + Automatically calculate spline parameters?:Yes + Background mode:auto + Number of spline points:5 + Background threshold:2.0 + Image resampling factor:2.0 + Maximum number of iterations:40 + Residual value for convergence:0.001 + +CorrectIlluminationApply:[module_num:9|svn_version:'Unknown'|variable_revision_number:5|show_window:False|notes:['Apply illumination correction functions to all channel groups']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the input image:OrigDAPI + Name the output image:CorrDAPI + Select the illumination function:IllumDAPI + Select how the illumination function is applied:Subtract + Select the input image:OrigGFP + Name the output image:CorrGFP + Select the illumination function:IllumGFP + Select how the illumination function is applied:Subtract + Select the input image:OrigRFP + Name the output image:CorrRFP + Select the illumination function:IllumRFP + Select how the illumination function is applied:Subtract + Select the input image:OrigMito + Name the output image:CorrMito + Select the illumination function:IllumMito + Select how the illumination function is applied:Subtract + Set output image values less than 0 equal to 0?:Yes + Set output image values greater than 1 equal to 1?:Yes + +SaveImages:[module_num:10|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:['Save DAPI images as same bit-depth']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the type of image to save:Image + Select the image to save:CorrDAPI + Select method for constructing file names:From image filename + Select image name for file prefix:OrigDAPI + Enter single file name:OrigBlue + Number of digits:4 + Append a suffix to the image file name?:Yes + Text to append to the image name:_illumcorrect + Saved file format:tiff + Output file location:Default Output Folder|Desktop/GitHub Repos/nf1_cellpainting_data/1.cellprofiler_ic/2000_density_test_IC + Image bit depth:16-bit integer + Overwrite existing files without warning?:Yes + When to save:Every cycle + Record the file and path information to the saved image?:No + Create subfolders in the output folder?:No + Base image folder:Elsewhere...| + How to save the series:T (Time) + Save with lossless compression?:Yes + +SaveImages:[module_num:11|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:['Save GFP images as same bit-depth']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the type of image to save:Image + Select the image to save:CorrGFP + Select method for constructing file names:From image filename + Select image name for file prefix:OrigGFP + Enter single file name:OrigBlue + Number of digits:4 + Append a suffix to the image file name?:Yes + Text to append to the image name:_illumcorrect + Saved file format:tiff + Output file location:Default Output Folder|Desktop/GitHub Repos/nf1_cellpainting_data/1.cellprofiler_ic/2000_density_test_IC + Image bit depth:16-bit integer + Overwrite existing files without warning?:Yes + When to save:Every cycle + Record the file and path information to the saved image?:No + Create subfolders in the output folder?:No + Base image folder:Elsewhere...| + How to save the series:T (Time) + Save with lossless compression?:Yes + +SaveImages:[module_num:12|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:['Save RFP images as same bit-depth']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the type of image to save:Image + Select the image to save:CorrRFP + Select method for constructing file names:From image filename + Select image name for file prefix:OrigRFP + Enter single file name:OrigBlue + Number of digits:4 + Append a suffix to the image file name?:Yes + Text to append to the image name:_illumcorrect + Saved file format:tiff + Output file location:Default Output Folder|Desktop/GitHub Repos/nf1_cellpainting_data/1.cellprofiler_ic/2000_density_test_IC + Image bit depth:16-bit integer + Overwrite existing files without warning?:Yes + When to save:Every cycle + Record the file and path information to the saved image?:No + Create subfolders in the output folder?:No + Base image folder:Elsewhere...| + How to save the series:T (Time) + Save with lossless compression?:Yes + +SaveImages:[module_num:13|svn_version:'Unknown'|variable_revision_number:16|show_window:False|notes:['Save CY5 images as the same bit-deph']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] + Select the type of image to save:Image + Select the image to save:CorrMito + Select method for constructing file names:From image filename + Select image name for file prefix:OrigMito + Enter single file name:OrigBlue + Number of digits:4 + Append a suffix to the image file name?:Yes + Text to append to the image name:_illumcorrect + Saved file format:tiff + Output file location:Default Output Folder|Desktop/GitHub Repos/nf1_cellpainting_data/1.cellprofiler_ic/2000_density_test_IC + Image bit depth:16-bit integer + Overwrite existing files without warning?:Yes + When to save:Every cycle + Record the file and path information to the saved image?:No + Create subfolders in the output folder?:No + Base image folder:Elsewhere...| + How to save the series:T (Time) + Save with lossless compression?:Yes diff --git a/1.cellprofiler_ic/NF1_illum.cppipe b/1.cellprofiler_ic/NF1_illum_Plates_1_2.cppipe similarity index 100% rename from 1.cellprofiler_ic/NF1_illum.cppipe rename to 1.cellprofiler_ic/NF1_illum_Plates_1_2.cppipe diff --git a/1.cellprofiler_ic/nf1_ic.ipynb b/1.cellprofiler_ic/nf1_ic.ipynb index 76ecc77..059060b 100644 --- a/1.cellprofiler_ic/nf1_ic.ipynb +++ b/1.cellprofiler_ic/nf1_ic.ipynb @@ -43,16 +43,21 @@ "metadata": {}, "outputs": [], "source": [ - "path_to_pipeline = pathlib.Path(\"NF1_illum.cppipe\").absolute()\n", - "\n", "plates_info_dictionary = {\n", " \"Plate_1\": {\n", - " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_1/\").absolute(),\n", - " \"path_to_output\": pathlib.Path(\"Corrected_Plate_1\").absolute(),\n", + " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plates_1_2.cppipe\").absolute().resolve(),\n", + " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_1/\").absolute().resolve(),\n", + " \"path_to_output\": pathlib.Path(\"Corrected_Plate_1\").absolute().resolve(),\n", " },\n", " \"Plate_2\": {\n", - " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_2/\").absolute(),\n", - " \"path_to_output\": pathlib.Path(\"Corrected_Plate_2\").absolute(),\n", + " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plates_1_2.cppipe\").absolute().resolve(),\n", + " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_2/\").absolute().resolve(),\n", + " \"path_to_output\": pathlib.Path(\"Corrected_Plate_2\").absolute().resolve(),\n", + " },\n", + " \"Plate_3\": {\n", + " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plate3.cppipe\").absolute().resolve(),\n", + " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_3/\").absolute().resolve(),\n", + " \"path_to_output\": pathlib.Path(\"Corrected_Plate_3\").absolute().resolve(),\n", " },\n", "}" ] @@ -62,7 +67,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Run illumination correction pipeline on each plate" + "## Run illumination correction pipeline on each plate\n", + "\n", + "In this notebook, we do not run the cells to completion as we prefer to run the notebooks as nbconverted python files due to better stability." ] }, { @@ -75,13 +82,37 @@ "output_type": "stream", "text": [ "Correcting Plate_1\n", - "Correcting Plate_2\n" + "Starting CellProfiler run on Plate_1\n", + "The CellProfiler run has been completed with Plate_1. Please check log file for any errors.\n", + "Correcting Plate_2\n", + "Starting CellProfiler run on Plate_2\n", + "The CellProfiler run has been completed with Plate_2. Please check log file for any errors.\n", + "Correcting Plate_3\n", + "Starting CellProfiler run on Plate_3\n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[3], line 9\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mCorrecting \u001b[39m\u001b[39m{\u001b[39;00mplate\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[1;32m 8\u001b[0m \u001b[39m# run illumination correction pipeline and save images\u001b[39;00m\n\u001b[0;32m----> 9\u001b[0m cp_utils\u001b[39m.\u001b[39;49mrun_cellprofiler(\n\u001b[1;32m 10\u001b[0m path_to_pipeline\u001b[39m=\u001b[39;49mpath_to_pipeline,\n\u001b[1;32m 11\u001b[0m path_to_output\u001b[39m=\u001b[39;49mpath_to_output,\n\u001b[1;32m 12\u001b[0m path_to_images\u001b[39m=\u001b[39;49mpath_to_images,\n\u001b[1;32m 13\u001b[0m \u001b[39m# these variables are turned off for illum pipeline\u001b[39;49;00m\n\u001b[1;32m 14\u001b[0m sqlite_name\u001b[39m=\u001b[39;49m\u001b[39mNone\u001b[39;49;00m,\n\u001b[1;32m 15\u001b[0m analysis_run\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[1;32m 16\u001b[0m )\n", + "File \u001b[0;32m~/Desktop/GitHub_Repos/nf1_cellpainting_data/1.cellprofiler_ic/../utils/cp_utils.py:98\u001b[0m, in \u001b[0;36mrun_cellprofiler\u001b[0;34m(path_to_pipeline, path_to_output, path_to_images, sqlite_name, analysis_run)\u001b[0m\n\u001b[1;32m 80\u001b[0m \u001b[39mwith\u001b[39;00m \u001b[39mopen\u001b[39m(\n\u001b[1;32m 81\u001b[0m pathlib\u001b[39m.\u001b[39mPath(\n\u001b[1;32m 82\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mlogs/cellprofiler_output_\u001b[39m\u001b[39m{\u001b[39;00mpathlib\u001b[39m.\u001b[39mPath(path_to_images)\u001b[39m.\u001b[39mname\u001b[39m}\u001b[39;00m\u001b[39m.log\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 85\u001b[0m ) \u001b[39mas\u001b[39;00m cellprofiler_output_file:\n\u001b[1;32m 86\u001b[0m \u001b[39m# run CellProfiler for a illumination correction pipeline\u001b[39;00m\n\u001b[1;32m 87\u001b[0m command \u001b[39m=\u001b[39m [\n\u001b[1;32m 88\u001b[0m \u001b[39m\"\u001b[39m\u001b[39mcellprofiler\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m 89\u001b[0m \u001b[39m\"\u001b[39m\u001b[39m-c\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 96\u001b[0m path_to_images,\n\u001b[1;32m 97\u001b[0m ]\n\u001b[0;32m---> 98\u001b[0m subprocess\u001b[39m.\u001b[39;49mrun(\n\u001b[1;32m 99\u001b[0m command,\n\u001b[1;32m 100\u001b[0m stdout\u001b[39m=\u001b[39;49mcellprofiler_output_file,\n\u001b[1;32m 101\u001b[0m stderr\u001b[39m=\u001b[39;49mcellprofiler_output_file,\n\u001b[1;32m 102\u001b[0m check\u001b[39m=\u001b[39;49m\u001b[39mTrue\u001b[39;49;00m,\n\u001b[1;32m 103\u001b[0m )\n\u001b[1;32m 104\u001b[0m \u001b[39mprint\u001b[39m(\n\u001b[1;32m 105\u001b[0m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mThe CellProfiler run has been completed with \u001b[39m\u001b[39m{\u001b[39;00mpathlib\u001b[39m.\u001b[39mPath(path_to_images)\u001b[39m.\u001b[39mname\u001b[39m}\u001b[39;00m\u001b[39m. Please check log file for any errors.\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 106\u001b[0m )\n\u001b[1;32m 108\u001b[0m \u001b[39m# run CellProfiler analysis pipeline\u001b[39;00m\n", + "File \u001b[0;32m~/opt/anaconda3/envs/nf1_cellpainting_data/lib/python3.8/subprocess.py:495\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m 493\u001b[0m \u001b[39mwith\u001b[39;00m Popen(\u001b[39m*\u001b[39mpopenargs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs) \u001b[39mas\u001b[39;00m process:\n\u001b[1;32m 494\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 495\u001b[0m stdout, stderr \u001b[39m=\u001b[39m process\u001b[39m.\u001b[39;49mcommunicate(\u001b[39minput\u001b[39;49m, timeout\u001b[39m=\u001b[39;49mtimeout)\n\u001b[1;32m 496\u001b[0m \u001b[39mexcept\u001b[39;00m TimeoutExpired \u001b[39mas\u001b[39;00m exc:\n\u001b[1;32m 497\u001b[0m process\u001b[39m.\u001b[39mkill()\n", + "File \u001b[0;32m~/opt/anaconda3/envs/nf1_cellpainting_data/lib/python3.8/subprocess.py:1020\u001b[0m, in \u001b[0;36mPopen.communicate\u001b[0;34m(self, input, timeout)\u001b[0m\n\u001b[1;32m 1018\u001b[0m stderr \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstderr\u001b[39m.\u001b[39mread()\n\u001b[1;32m 1019\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mstderr\u001b[39m.\u001b[39mclose()\n\u001b[0;32m-> 1020\u001b[0m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mwait()\n\u001b[1;32m 1021\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m 1022\u001b[0m \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/opt/anaconda3/envs/nf1_cellpainting_data/lib/python3.8/subprocess.py:1083\u001b[0m, in \u001b[0;36mPopen.wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 1081\u001b[0m endtime \u001b[39m=\u001b[39m _time() \u001b[39m+\u001b[39m timeout\n\u001b[1;32m 1082\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 1083\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_wait(timeout\u001b[39m=\u001b[39;49mtimeout)\n\u001b[1;32m 1084\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mKeyboardInterrupt\u001b[39;00m:\n\u001b[1;32m 1085\u001b[0m \u001b[39m# https://bugs.python.org/issue25942\u001b[39;00m\n\u001b[1;32m 1086\u001b[0m \u001b[39m# The first keyboard interrupt waits briefly for the child to\u001b[39;00m\n\u001b[1;32m 1087\u001b[0m \u001b[39m# exit under the common assumption that it also received the ^C\u001b[39;00m\n\u001b[1;32m 1088\u001b[0m \u001b[39m# generated SIGINT and will exit rapidly.\u001b[39;00m\n\u001b[1;32m 1089\u001b[0m \u001b[39mif\u001b[39;00m timeout \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/opt/anaconda3/envs/nf1_cellpainting_data/lib/python3.8/subprocess.py:1806\u001b[0m, in \u001b[0;36mPopen._wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 1804\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mreturncode \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m 1805\u001b[0m \u001b[39mbreak\u001b[39;00m \u001b[39m# Another thread waited.\u001b[39;00m\n\u001b[0;32m-> 1806\u001b[0m (pid, sts) \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_try_wait(\u001b[39m0\u001b[39;49m)\n\u001b[1;32m 1807\u001b[0m \u001b[39m# Check the pid and loop as waitpid has been known to\u001b[39;00m\n\u001b[1;32m 1808\u001b[0m \u001b[39m# return 0 even without WNOHANG in odd situations.\u001b[39;00m\n\u001b[1;32m 1809\u001b[0m \u001b[39m# http://bugs.python.org/issue14396.\u001b[39;00m\n\u001b[1;32m 1810\u001b[0m \u001b[39mif\u001b[39;00m pid \u001b[39m==\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpid:\n", + "File \u001b[0;32m~/opt/anaconda3/envs/nf1_cellpainting_data/lib/python3.8/subprocess.py:1764\u001b[0m, in \u001b[0;36mPopen._try_wait\u001b[0;34m(self, wait_flags)\u001b[0m\n\u001b[1;32m 1762\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"All callers to this function MUST hold self._waitpid_lock.\"\"\"\u001b[39;00m\n\u001b[1;32m 1763\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 1764\u001b[0m (pid, sts) \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39;49mwaitpid(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mpid, wait_flags)\n\u001b[1;32m 1765\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mChildProcessError\u001b[39;00m:\n\u001b[1;32m 1766\u001b[0m \u001b[39m# This happens if SIGCLD is set to be ignored or waiting\u001b[39;00m\n\u001b[1;32m 1767\u001b[0m \u001b[39m# for child processes has otherwise been disabled for our\u001b[39;00m\n\u001b[1;32m 1768\u001b[0m \u001b[39m# process. This child is dead, we can't get the status.\u001b[39;00m\n\u001b[1;32m 1769\u001b[0m pid \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpid\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ "# run through each plate with each set of paths based on dictionary\n", "for plate, info in plates_info_dictionary.items():\n", + " path_to_pipeline = info[\"path_to_pipeline\"]\n", " path_to_output = info[\"path_to_output\"]\n", " path_to_images = info[\"path_to_images\"]\n", " print(f\"Correcting {plate}\")\n", From e57de3e877844e94757a13843745fb7644279f02 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Wed, 12 Apr 2023 15:03:47 -0600 Subject: [PATCH 10/15] add to gitignore to ignore new corrected plate 3 --- .gitignore | 1 + 1 file changed, 1 insertion(+) diff --git a/.gitignore b/.gitignore index 2e514f2..bbf936e 100644 --- a/.gitignore +++ b/.gitignore @@ -9,6 +9,7 @@ __pycache__ # 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 From 3787a88ad3bd69d27a73694c446a4ad8ca900859 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Thu, 13 Apr 2023 08:57:49 -0600 Subject: [PATCH 11/15] add nbconverted py file and edit doc to sh file --- 1.cellprofiler_ic/nf1_ic.sh | 2 +- 1.cellprofiler_ic/scripts/nf1_ic.py | 20 ++++++++++++++------ 2 files changed, 15 insertions(+), 7 deletions(-) diff --git a/1.cellprofiler_ic/nf1_ic.sh b/1.cellprofiler_ic/nf1_ic.sh index 5a49488..f562819 100644 --- a/1.cellprofiler_ic/nf1_ic.sh +++ b/1.cellprofiler_ic/nf1_ic.sh @@ -1,6 +1,6 @@ #!/bin/bash -# activate the main conda environment +# activate the main conda environment (if not already activated) eval "$(conda shell.bash hook)" conda activate nf1_cellpainting_data diff --git a/1.cellprofiler_ic/scripts/nf1_ic.py b/1.cellprofiler_ic/scripts/nf1_ic.py index 04713cb..e6cf50a 100644 --- a/1.cellprofiler_ic/scripts/nf1_ic.py +++ b/1.cellprofiler_ic/scripts/nf1_ic.py @@ -20,27 +20,35 @@ # In[2]: -path_to_pipeline = pathlib.Path("NF1_illum.cppipe").absolute() - plates_info_dictionary = { "Plate_1": { - "path_to_images": pathlib.Path("../0.download_data/Plate_1/").absolute(), - "path_to_output": pathlib.Path("Corrected_Plate_1").absolute(), + "path_to_pipeline": pathlib.Path("NF1_illum_Plates_1_2.cppipe").absolute().resolve(), + "path_to_images": pathlib.Path("../0.download_data/Plate_1/").absolute().resolve(), + "path_to_output": pathlib.Path("Corrected_Plate_1").absolute().resolve(), }, "Plate_2": { - "path_to_images": pathlib.Path("../0.download_data/Plate_2/").absolute(), - "path_to_output": pathlib.Path("Corrected_Plate_2").absolute(), + "path_to_pipeline": pathlib.Path("NF1_illum_Plates_1_2.cppipe").absolute().resolve(), + "path_to_images": pathlib.Path("../0.download_data/Plate_2/").absolute().resolve(), + "path_to_output": pathlib.Path("Corrected_Plate_2").absolute().resolve(), + }, + "Plate_3": { + "path_to_pipeline": pathlib.Path("NF1_illum_Plate3.cppipe").absolute().resolve(), + "path_to_images": pathlib.Path("../0.download_data/Plate_3/").absolute().resolve(), + "path_to_output": pathlib.Path("Corrected_Plate_3").absolute().resolve(), }, } # ## Run illumination correction pipeline on each plate +# +# In this notebook, we do not run the cells to completion as we prefer to run the notebooks as nbconverted python files due to better stability. # In[3]: # run through each plate with each set of paths based on dictionary for plate, info in plates_info_dictionary.items(): + path_to_pipeline = info["path_to_pipeline"] path_to_output = info["path_to_output"] path_to_images = info["path_to_images"] print(f"Correcting {plate}") From 59ff3fa30cbb7564193233c269978d4734184345 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Thu, 13 Apr 2023 09:02:14 -0600 Subject: [PATCH 12/15] add comp time for ic processing and os system --- 1.cellprofiler_ic/README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/1.cellprofiler_ic/README.md b/1.cellprofiler_ic/README.md index 0f4aaad..3032607 100644 --- a/1.cellprofiler_ic/README.md +++ b/1.cellprofiler_ic/README.md @@ -14,3 +14,5 @@ cd 1.cellprofiler_ic # run the notebook as a python script bash nf1_ic.sh ``` + +For three plates, it took about 18 hours to calculate and save illumination corrected images on a computer using MacOS Ventura 13.2.1 with the M2 chip. From bba1f03707a1e6adb6fa16bbedbd7137a606272c Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Thu, 13 Apr 2023 11:48:08 -0600 Subject: [PATCH 13/15] Correct resolve for paths in ic notebook --- 1.cellprofiler_ic/nf1_ic.ipynb | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/1.cellprofiler_ic/nf1_ic.ipynb b/1.cellprofiler_ic/nf1_ic.ipynb index 059060b..8ab0f31 100644 --- a/1.cellprofiler_ic/nf1_ic.ipynb +++ b/1.cellprofiler_ic/nf1_ic.ipynb @@ -45,19 +45,19 @@ "source": [ "plates_info_dictionary = {\n", " \"Plate_1\": {\n", - " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plates_1_2.cppipe\").absolute().resolve(),\n", - " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_1/\").absolute().resolve(),\n", - " \"path_to_output\": pathlib.Path(\"Corrected_Plate_1\").absolute().resolve(),\n", + " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plates_1_2.cppipe\").resolve(strict=True),\n", + " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_1/\").resolve(strict=True),\n", + " \"path_to_output\": pathlib.Path(\"Corrected_Plate_1\").resolve(strict=True),\n", " },\n", " \"Plate_2\": {\n", - " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plates_1_2.cppipe\").absolute().resolve(),\n", - " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_2/\").absolute().resolve(),\n", - " \"path_to_output\": pathlib.Path(\"Corrected_Plate_2\").absolute().resolve(),\n", + " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plates_1_2.cppipe\").resolve(strict=True),\n", + " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_2/\").resolve(strict=True),\n", + " \"path_to_output\": pathlib.Path(\"Corrected_Plate_2\").resolve(strict=True),\n", " },\n", " \"Plate_3\": {\n", - " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plate3.cppipe\").absolute().resolve(),\n", - " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_3/\").absolute().resolve(),\n", - " \"path_to_output\": pathlib.Path(\"Corrected_Plate_3\").absolute().resolve(),\n", + " \"path_to_pipeline\": pathlib.Path(\"NF1_illum_Plate3.cppipe\").resolve(strict=True),\n", + " \"path_to_images\": pathlib.Path(\"../0.download_data/Plate_3/\").resolve(strict=True),\n", + " \"path_to_output\": pathlib.Path(\"Corrected_Plate_3\").resolve(strict=True),\n", " },\n", "}" ] From e78c1b74d4484beceb20ad08b509a52ab629832a Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Thu, 13 Apr 2023 11:53:30 -0600 Subject: [PATCH 14/15] correct the checks for pipeline and images --- utils/cp_utils.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/utils/cp_utils.py b/utils/cp_utils.py index d0eec46..908df49 100644 --- a/utils/cp_utils.py +++ b/utils/cp_utils.py @@ -60,11 +60,11 @@ def run_cellprofiler( multiple sets of images (e.g., per plate) so that the outputs will have different names (default is None) analysis_run (bool, optional): will use functions to complete an analysis pipeline (default is False) """ - # check to make sure paths to pipeline and images are correct before running the pipeline - if not os.path.exists(path_to_pipeline): - raise FileNotFoundError(f"Directory '{path_to_pipeline}' does not exist") - if not os.path.exists(path_to_images): - raise FileNotFoundError(f"Directory '{path_to_images}' does not exist") + # check to make sure paths to pipeline and directory of images are correct before running the pipeline + if not pathlib.Path(path_to_pipeline): + raise FileNotFoundError(f"The file '{pathlib.Path(path_to_pipeline).name}' does not exist") + if not pathlib.Path(path_to_images).is_dir(): + raise FileNotFoundError(f"Directory '{pathlib.Path(path_to_images).name}' does not exist or is not a directory") # make logs directory log_dir = pathlib.Path("./logs") From dcfbbba501a8107fabbdcb8ba1176b571cbea341 Mon Sep 17 00:00:00 2001 From: Jenna Tomkinson Date: Thu, 13 Apr 2023 11:54:35 -0600 Subject: [PATCH 15/15] fix red error for no newline --- 0.download_data/metadata/barcode_platemap.csv | 2 +- 0.download_data/metadata/platemap_NF1_plate3.csv | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/0.download_data/metadata/barcode_platemap.csv b/0.download_data/metadata/barcode_platemap.csv index e210270..a09e81f 100644 --- a/0.download_data/metadata/barcode_platemap.csv +++ b/0.download_data/metadata/barcode_platemap.csv @@ -1,4 +1,4 @@ Assay_Plate_Barcode,Plate_Map_Name plate_1,platemap_NF1_plate1 plate_2,platemap_NF1_plate2 -plate_3,platemap_NF1_plate3 \ No newline at end of file +plate_3,platemap_NF1_plate3 diff --git a/0.download_data/metadata/platemap_NF1_plate3.csv b/0.download_data/metadata/platemap_NF1_plate3.csv index 0ab91cd..91d7913 100644 --- a/0.download_data/metadata/platemap_NF1_plate3.csv +++ b/0.download_data/metadata/platemap_NF1_plate3.csv @@ -70,4 +70,4 @@ 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 \ No newline at end of file +G,12,G12,NF1,NULL,4000

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