Sync dev with latest

.gitignore

@@ -7,3 +7,7 @@ processor/application_default_credentials.json
 processor/.env
 processor/helpers/__pycache__/
 processor/.DS_Store
+processor/samples/
+application_default_credentials.json
+server/.env
+client/yarn.lock

Dockerfile

@@ -0,0 +1,27 @@
+ARG NODE_PARENT=node:20
+
+FROM  ${NODE_PARENT} as frontend
+ARG BUILD_MODE=prod
+ENV BUILDDIR=/app
+
+WORKDIR ${BUILDDIR}
+COPY client/package.json ${BUILDDIR}
+COPY client/package-lock.json ${BUILDDIR}
+COPY nginx/default.conf ${BUILDDIR}
+
+RUN npm install  --legacy-peer-deps
+COPY ./client/ ${BUILDDIR}
+RUN npx update-browserslist-db@latest
+
+RUN echo "Build mode is: ${BUILD_MODE}"
+RUN npm run build:${BUILD_MODE}
+
+FROM nginx:1.19.3-alpine
+
+RUN cat /etc/nginx/conf.d/default.conf
+
+COPY --from=frontend /app/default.conf  /etc/nginx/conf.d/default.conf
+
+COPY --from=frontend /app/build /usr/share/nginx/html/
+
+EXPOSE 80

README.md

@@ -17,7 +17,7 @@ cd processor
 mkdir data
 ```
 
-Inside the data folder create 2 more folders, one to store all the activity maps (ActivityMap) )and one to store all the atlases (Atlas).
+Inside the data folder create 2 more folders, one to store all the activity maps (ActivityMap) and one to store all the atlases (Atlas).
 
 ```
 cd data
@@ -32,9 +32,15 @@ cp *atlas.nii.gz ./Atlas/
 cp *maps.nii.gz ./ActivityMap/
 ```
 
-#### Prepare the index.json inside the data folder
+For each atlas file copied inside the Atlas folder, copy also the wireframe version being sure to use the same file name followed by a capital W before the dot extension of the atlas.
 
-It is responsability of the user triggering the ingestion also to prepare a file, **named index.json and placed inside the data folder**, that contains the hierarchical structure of the experiments and the data, according to the data model documented for the project.
+```Example: if the atlas file is gubra_ano_combined_25um.nii.gz the wireframe file should be called gubra_ano_combined_25umW.nii.gz (capital W before the .nii.gz).```
+
+#### Prepare the index.json and metadata.json inside the data folder
+
+It is responsibility of the user triggering the ingestion also to prepare a file, named **index.json** and a file named **metadata.json**,
+both placed inside the data folder, that contains the hierarchical structure of the experiments and the data, according to the data model documented for the project 
+and experiments metadata respectively.
 
 Below an example of a working index.json file used during development:
 
@@ -119,6 +125,115 @@ Below an example of a working index.json file used during development:
 }
 ```
 
+Below an example of a working metadata.json file used during development:
+
+```json
+{
+    "MDMA (social context) maps": {
+        "Experiment Name": "Effect of psilocybin on c-Fos-IF in distinct contexts",
+        "Contributor": "Boris Heifets (Stanford University)",
+        "Publications": [{
+            "link": "https://google.com",
+            "label": "UNRAVELing the synergistic effects of psilocybin and environment on brain-wide immediate early gene expression in mice",
+            "description": "",
+            "keywords": "Rijsketic DR*, Casey AB*, Barbosa DA, Zhang X, Hietamies TM, Ramirez-Ovalle G, Pomrenze MB, Halpern CH, Williams LM, Malenka RC, Heifets BD",
+            "tags": [
+                "rabbit anti-cfos", "donkey anti-Rabbit Alexa647"
+            ]
+        }],
+        "Treatment/Condition(s)": "psilocybin vs. saline; home cage (HC) vs. enriched environment (EE)",
+        "Dose(s)": "psilocybin (2 mg/kg, i.p.); 4-OHT (50 mg/kg; i.p.)",
+        "Species, strain, gene(s)": "TRAP2+/-;Ai14+ mice (bred to C57BL/6)",
+        "Sample sizes(s)": "n=9 for saline (HC); n = 8 for psilocybin (HC); n = 9 for saline (EE); n = 7 for psilocybin EE",
+        "Clearing method": "iDISCO+",
+        "Imaging modality": "light sheet fluorescent microscopy (LSFM)",
+        "Experiment details": "For TRAPing, mice were injected with 4-OHT and psilocybin or saline. Two-weeks later, mice were again injected with psilocybin or saline (crossover design) and placed in their assigned context for 2 hours before fixation for c-Fos mapping. Brains were hemisected, immunostained, cleared, and imaged in 3D with a Zeiss Lightsheet 7 (2.5x objective; 0.52x zoom; 3.5 isotropic resolution; 10.61 µm sheet thickness). 488 nm light excited autofluorescence (8% of 30 mW; 505-530 nm; 50 ms). 638 nm light excited IF (20% of 75 mW; 660 nm long pass; 50 ms). Pivot scanning limited artifacts. Tiled z-stacks (10% overlap) were stitched in Zen Blue.",
+        "Image analysis": [{
+            "link": "https://google.com",
+            "label": "UNRAVEL Github repository",
+            "description": "We developed UNRAVEL to automate c-Fos mapping. Downsampled autofluorescence images were registered (MIRACL) to an iDISCO+/LSFM version of the Allen brain atlas (CCFv3). c-Fos-IF images were rolling ball background subtracted (4-pixel radius), warped to atlas space, z-scored, and smoothed (50 µm). Voxel-wise analyses were performed with randomise_parallel (FSL) according to a 2x2 ANOVA design (6,000 permutations). False positives in F-contrast maps were limited by false discovery rate (FDR) correction and cluster extent (> 100 voxels). Surviving clusters were warped to full resolution tissue space for post hoc cell density comparisons using cell segmentations from Ilastik.",
+            "keywords": "",
+            "tags": []
+        }],
+        "Additional links": [{
+            "link": "https://google.com",
+            "label": "Antibody registry",
+            "description": "Documents, documentations and repositories that relates to this experiment.",
+            "keywords": "",
+            "tags": []
+        }]
+    },
+    "Psilocybin (HC; EE) maps": {
+        "Experiment Name": "Effect of psilocybin on c-Fos-IF in distinct contexts",
+        "Contributor": "Boris Heifets (Stanford University)",
+        "Publications": [{
+            "link": "https://google.com",
+            "label": "UNRAVELing the synergistic effects of psilocybin and environment on brain-wide immediate early gene expression in mice",
+            "description": "",
+            "keywords": "Rijsketic DR*, Casey AB*, Barbosa DA, Zhang X, Hietamies TM, Ramirez-Ovalle G, Pomrenze MB, Halpern CH, Williams LM, Malenka RC, Heifets BD",
+            "tags": [
+                "rabbit anti-cfos", "donkey anti-Rabbit Alexa647"
+            ]
+        }],
+        "Treatment/Condition(s)": "psilocybin vs. saline; home cage (HC) vs. enriched environment (EE)",
+        "Dose(s)": "psilocybin (2 mg/kg, i.p.); 4-OHT (50 mg/kg; i.p.)",
+        "Species, strain, gene(s)": "TRAP2+/-;Ai14+ mice (bred to C57BL/6)",
+        "Sample sizes(s)": "n=9 for saline (HC); n = 8 for psilocybin (HC); n = 9 for saline (EE); n = 7 for psilocybin EE",
+        "Clearing method": "iDISCO+",
+        "Imaging modality": "light sheet fluorescent microscopy (LSFM)",
+        "Experiment details": "For TRAPing, mice were injected with 4-OHT and psilocybin or saline. Two-weeks later, mice were again injected with psilocybin or saline (crossover design) and placed in their assigned context for 2 hours before fixation for c-Fos mapping. Brains were hemisected, immunostained, cleared, and imaged in 3D with a Zeiss Lightsheet 7 (2.5x objective; 0.52x zoom; 3.5 isotropic resolution; 10.61 µm sheet thickness). 488 nm light excited autofluorescence (8% of 30 mW; 505-530 nm; 50 ms). 638 nm light excited IF (20% of 75 mW; 660 nm long pass; 50 ms). Pivot scanning limited artifacts. Tiled z-stacks (10% overlap) were stitched in Zen Blue.",
+        "Image analysis": [{
+            "link": "https://google.com",
+            "label": "UNRAVEL Github repository",
+            "description": "We developed UNRAVEL to automate c-Fos mapping. Downsampled autofluorescence images were registered (MIRACL) to an iDISCO+/LSFM version of the Allen brain atlas (CCFv3). c-Fos-IF images were rolling ball background subtracted (4-pixel radius), warped to atlas space, z-scored, and smoothed (50 µm). Voxel-wise analyses were performed with randomise_parallel (FSL) according to a 2x2 ANOVA design (6,000 permutations). False positives in F-contrast maps were limited by false discovery rate (FDR) correction and cluster extent (> 100 voxels). Surviving clusters were warped to full resolution tissue space for post hoc cell density comparisons using cell segmentations from Ilastik.",
+            "keywords": "",
+            "tags": []
+        }],
+        "Additional links": [{
+            "link": "https://google.com",
+            "label": "Antibody registry",
+            "description": "Documents, documentations and repositories that relates to this experiment.",
+            "keywords": "",
+            "tags": []
+        }]
+    },
+    "Ketamine v. Naltrexone+Ket maps": {
+        "Experiment Name": "Effect of psilocybin on c-Fos-IF in distinct contexts",
+        "Contributor": "Boris Heifets (Stanford University)",
+        "Publications": [{
+            "link": "https://google.com",
+            "label": "UNRAVELing the synergistic effects of psilocybin and environment on brain-wide immediate early gene expression in mice",
+            "description": "",
+            "keywords": "Rijsketic DR*, Casey AB*, Barbosa DA, Zhang X, Hietamies TM, Ramirez-Ovalle G, Pomrenze MB, Halpern CH, Williams LM, Malenka RC, Heifets BD",
+            "tags": [
+                "rabbit anti-cfos", "donkey anti-Rabbit Alexa647"
+            ]
+        }],
+        "Treatment/Condition(s)": "psilocybin vs. saline; home cage (HC) vs. enriched environment (EE)",
+        "Dose(s)": "psilocybin (2 mg/kg, i.p.); 4-OHT (50 mg/kg; i.p.)",
+        "Species, strain, gene(s)": "TRAP2+/-;Ai14+ mice (bred to C57BL/6)",
+        "Sample sizes(s)": "n=9 for saline (HC); n = 8 for psilocybin (HC); n = 9 for saline (EE); n = 7 for psilocybin EE",
+        "Clearing method": "iDISCO+",
+        "Imaging modality": "light sheet fluorescent microscopy (LSFM)",
+        "Experiment details": "For TRAPing, mice were injected with 4-OHT and psilocybin or saline. Two-weeks later, mice were again injected with psilocybin or saline (crossover design) and placed in their assigned context for 2 hours before fixation for c-Fos mapping. Brains were hemisected, immunostained, cleared, and imaged in 3D with a Zeiss Lightsheet 7 (2.5x objective; 0.52x zoom; 3.5 isotropic resolution; 10.61 µm sheet thickness). 488 nm light excited autofluorescence (8% of 30 mW; 505-530 nm; 50 ms). 638 nm light excited IF (20% of 75 mW; 660 nm long pass; 50 ms). Pivot scanning limited artifacts. Tiled z-stacks (10% overlap) were stitched in Zen Blue.",
+        "Image analysis": [{
+            "link": "https://google.com",
+            "label": "UNRAVEL Github repository",
+            "description": "We developed UNRAVEL to automate c-Fos mapping. Downsampled autofluorescence images were registered (MIRACL) to an iDISCO+/LSFM version of the Allen brain atlas (CCFv3). c-Fos-IF images were rolling ball background subtracted (4-pixel radius), warped to atlas space, z-scored, and smoothed (50 µm). Voxel-wise analyses were performed with randomise_parallel (FSL) according to a 2x2 ANOVA design (6,000 permutations). False positives in F-contrast maps were limited by false discovery rate (FDR) correction and cluster extent (> 100 voxels). Surviving clusters were warped to full resolution tissue space for post hoc cell density comparisons using cell segmentations from Ilastik.",
+            "keywords": "",
+            "tags": []
+        }],
+        "Additional links": [{
+            "link": "https://google.com",
+            "label": "Antibody registry",
+            "description": "Documents, documentations and repositories that relates to this experiment.",
+            "keywords": "",
+            "tags": []
+        }]
+    }
+}
+````
+
 #### Create a conda environment and install the required dependencies
 
 Create a conda environment and install all the required dependencies for the ingestion, using the file all_requirements.txt inside the processor folder.
@@ -152,16 +267,14 @@ To run this last step ensure to have the conda environment created above activat
 ```
 cd processor/
 python main.py
-
 ```
 
 The ingestion will take some time, which depends on the host machine running the ingestion and the connection/bandwidth used, since the steps performed are:
 
-- preprocess the nifti files to extract the msgpack equivalent, since it's way faster for the viewer handle these.
-- generate the wireframe for each atlas file.
+- preprocess the nifti files to extract the msgpack equivalent, since it's way faster for the viewer to handle these.
 - upload all the generated files in the bucket that stores the application data.
 
-## Setup development environment
+# For developers willing to contribute to the codebase - Setup development environment
 
 ### Backend
 

client/.env

@@ -1 +1 @@
-REACT_APP_SERVER_URL=https://storage.googleapis.com/cfos-visualizer-stanford
+REACT_APP_SERVER_URL=https://storage.googleapis.com/cfos-visualizer-stanford-dev

client/.env.development

@@ -0,0 +1 @@
+REACT_APP_SERVER_URL=https://storage.googleapis.com/cfos-visualizer-stanford-dev