Merging conflicts. Adding to main build process

Author: jjacobson95

.github/workflows/build.yml

@@ -177,6 +177,30 @@ jobs:
           push: true
           platforms: linux/amd64
 
+  build-pancpdo:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+      - name: Set up QEMU
+        uses: docker/setup-qemu-action@v3
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+      - name: Login to DockerHub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_PASSWORD }}
+      - name: Build and push pancpdo
+        uses: docker/build-push-action@v3
+        with:
+          file: ./build/docker/Dockerfile.pancpdo
+          tags: |
+            sgosline/pancpdo:latest
+            sgosline/pancpdo:${{ github.ref_name }}
+          push: true
+          platforms: linux/amd64
+
   build-upload:
     runs-on: ubuntu-latest
     steps:

.github/workflows/main.yml

@@ -4,6 +4,7 @@ on:
   push:
     tags:
           - '*'  # Triggers the workflow only on version tags
+  workflow_dispatch:  # Allows manual triggering of the workflow
 
 # Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
 permissions:
@@ -44,4 +45,4 @@ jobs:
     steps:
       - name: Deploy to GitHub Pages
         id: deployment
-        uses: actions/deploy-pages@v4
+        uses: actions/deploy-pages@v4

.gitignore

@@ -18,3 +18,5 @@ tests/__pycache__
 dist
 build/lib
 build/local
+coderdata/_version.py
+local/

README.md

@@ -1,5 +1,7 @@
 ## Cancer Omics Drug Experiment Response Dataset 
 
+
+
 There is a recent explosion of deep learning algorithms that to tackle the computational problem of predicting drug treatment outcome from baseline molecular measurements. To support this,we have built a benchmark dataset that harmonizes diverse datasets to better assess algorithm performance.
 
 This package collects diverse sets of paired molecular datasets with corresponding drug sensitivity data. All data here is reprocessed and standardized so it can be easily used as a benchmark dataset for the