Make GNN plots available as an SPT CLI command and API endpoint

analysis_replication/README.md

@@ -30,7 +30,7 @@ substituting the argument with the address of your local API server. (See *Setti
 - You can alternatively store the API host in `api_host.txt` and omit the command-line argument above.
 - The run result is here in [results.txt](results.txt).
 
-# Cell arrangment figure generation
+## Cell arrangement figure generation
 
 One figure is generated programmatically from published source TIFF files.
 To run the figure generation script, alter the command below to reference your own database configuration file and path to unzipped Moldoveanu et al dataset.
@@ -39,11 +39,11 @@ To run the figure generation script, alter the command below to reference your o
 python retrieve_example_plot.py dataset_directory/ ~/.spt_db.config
 ```
 
-# GNN importance fractions figure generation
+## GNN importance fractions figure generation
 
-Another figure is generated programmatically from extractions from Graph Neural Network models, provided by the API.
+This plot replication requires the installation of SPT, as it's not a script in this directory. Instead, it's a command in the `spt graphs` CLI that uses the configuration files stored in `gnn_figure/` to reproduce the plots seen in our publication.
 
 ```bash
-cd gnn_figure/
-python graph_plugin_plots.py
+spt graphs plot-importance-fractions --config_path gnn_figure/melanoma_intralesional_il2.config --output_filename gnn_figure/melanoma_intralesional_il2.png
+spt graphs plot-importance-fractions --config_path gnn_figure/urothelial_ici.config --output_filename gnn_figure/urothelial_ici.png
 ```

analysis_replication/gnn_figure/melanoma_intralesional_il2.config

@@ -0,0 +1,15 @@
+[general]
+study_name = Melanoma intralesional IL2
+
+[plot-importance-fractions]
+host_name = http://oncopathtk.org/api
+phenotypes = Tumor, Adipocyte or Langerhans cell, Natural killer cell, CD4+ T cell, Nerve, B cell, CD4+/CD8+ T cell, CD4+ regulatory T cell, CD8+ natural killer T cell, CD8+ regulatory T cell, CD8+ T cell, Double negative regulatory T cell, T cell/null phenotype, Natural killer T cell, CD4+ natural killer T cell
+plugins = cg-gnn, graph-transformer
+figure_size = 11, 8
+orientation = horizontal
+[plot-importance-fractions.cohort0]
+index_int = 1
+label = Non-responder
+[plot-importance-fractions.cohort1]
+index_int = 3
+label = Responder

analysis_replication/gnn_figure/urothelial_ici.config

@@ -0,0 +1,15 @@
+[general]
+study_name = Urothelial ICI
+
+[plot-importance-fractions]
+host_name = http://oncopathtk.org/api
+phenotypes = Tumor, CD4- CD8- T cell, T cytotoxic cell, T helper cell, Macrophage, intratumoral CD3+ LAG3+, Regulatory T cell
+plugins = cg-gnn, graph-transformer
+figure_size = 14, 5
+orientation = vertical
+[plot-importance-fractions.cohort0]
+index_int = 1
+label = Responder
+[plot-importance-fractions.cohort1]
+index_int = 2
+label = Non-responder

build/apiserver/Dockerfile

@@ -16,6 +16,7 @@ RUN python -m pip install scikit-learn==1.2.2
 RUN python -m pip install Pillow==9.5.0
 RUN python -m pip install pydantic==2.0.2
 RUN python -m pip install secure==0.3.0
+RUN python -m pip install matplotlib==3.7.1
 ARG version
 ARG service_name
 ARG WHEEL_FILENAME

build/apiserver/Makefile

@@ -81,4 +81,4 @@ ${TESTS}: setup-testing
 clean:
 >@rm -f ${WHEEL_FILENAME}
 >@rm -f status_code
->@for f in dlogs.db.txt dlogs.api.txt dlogs.od.txt ../../${TEST_LOCATION}\/${MODULE_NAME}/_proximity.json ../../${TEST_LOCATION}\/${MODULE_NAME}/_squidpy.json; do rm -f $$f; done;
+>@for f in dlogs.db.txt dlogs.api.txt dlogs.od.txt ../../${TEST_LOCATION}\/${MODULE_NAME}/_proximity.json ../../${TEST_LOCATION}\/${MODULE_NAME}/_squidpy.json ../../${TEST_LOCATION}\/${MODULE_NAME}/_gnn.svg ; do rm -f $$f; done;

build/build_scripts/.graph_transformer.config

@@ -0,0 +1,7 @@
+[general]
+db_config_file_path = build/db/.spt_db.config.local
+study_name = Melanoma intralesional IL2
+
+[upload-importances]
+plugin_used = graph-transformer
+datetime_of_run = 2023-10-02 10:46 AM

build/build_scripts/expected_table_counts.txt

@@ -9,15 +9,15 @@
                             diagnosis        2
        diagnostic_selection_criterion        4
             expression_quantification    18200
-                feature_specification        1
-                    feature_specifier        4
+                feature_specification        2
+                    feature_specifier        8
                histological_structure      700
 histological_structure_identification      700
          histology_assessment_process        7
                          intervention        2
    plane_coordinates_reference_system        0
                           publication        2
-           quantitative_feature_value      700
+           quantitative_feature_value     1400
                 research_professional       32
                            shape_file      700
           specimen_collection_process        7

build/build_scripts/import_test_dataset1.sh

@@ -10,8 +10,10 @@ nextflow run .
 rm -f .nextflow.log*; rm -rf .nextflow/; rm -f configure.sh; rm -f run.sh; rm -f main.nf; rm -f nextflow.config; rm -rf work/; rm -rf results/
 
 spt graphs upload-importances --config_path=build/build_scripts/.graph.config --importances_csv_path=test/test_data/gnn_importances/1.csv
+spt graphs upload-importances --config_path=build/build_scripts/.graph_transformer.config --importances_csv_path=test/test_data/gnn_importances/1.csv
 
-spt db upload-sync-findings --database-config-file=build/db/.spt_db.config.local test/test_data/findings.json
+spt db upload-sync-small --database-config-file=build/db/.spt_db.config.local findings test/test_data/findings.json
+spt db upload-sync-small --database-config-file=build/db/.spt_db.config.local gnn_plot_configurations test/test_data/gnn_plot.json
 
 spt db status --database-config-file build/db/.spt_db.config.local > table_counts.txt
 diff build/build_scripts/expected_table_counts.txt table_counts.txt

docs/maintenance.md

@@ -19,7 +19,9 @@ The modules in this repository are built, tested, and deployed using `make` and
 | [Docker Engine](https://docs.docker.com/engine/install/)   | 20.10.17                         |
 | [Docker Compose](https://docs.docker.com/compose/install/) | 2.10.2                           |
 | [bash](https://www.gnu.org/software/bash/)                 | >= 4                             |
-| [python](https://www.python.org/downloads/)                | >=3.7                            |
+| [python](https://www.python.org/downloads/)                | >=3.7 <3.12                      |
+| [postgresql](https://www.postgresql.org/download/)         | 13.4                             |
+| [toml](https://pypi.org/project/toml/)                     | 0.10.2                           |
 
 A typical development workflow looks like:
 

environment.yml

@@ -0,0 +1,6 @@
+name: spt
+channels:
+  - conda-forge
+dependencies:
+  - python=3.11
+  - libpq

pyproject.toml.unversioned

@@ -31,6 +31,7 @@ repository = "https://github.com/nadeemlab/SPT"
 
 [project.optional-dependencies]
 apiserver = [
+    "matplotlib==3.7.1",
     "fastapi==0.100.0",
     "uvicorn>=0.15.0,<0.16.0",
     "pandas==2.0.2",
@@ -190,7 +191,7 @@ packages = [
     "drop.py",
     "drop_ondemand_computations.py",
     "delete_feature.py",
-    "upload_sync_findings.py",
+    "upload_sync_small.py",
     "collection.py",
 ]
 "spatialprofilingtoolbox.db.data_model" = [
@@ -211,6 +212,7 @@ packages = [
     "extract.py",
     "finalize_graphs.py",
     "generate_graphs.py",
+    "plot_importance_fractions.py",
     "plot_interactives.py",
     "prepare_graph_creation.py",
     "upload_importances.py",