padding

.github/workflows/docker-image.yml

@@ -0,0 +1,33 @@
+name: Docker Build
+
+on:
+  push:
+    branches:
+      - release
+  build:
+    needs: test
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Build and push
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          push: true
+          tags: |
+            ghcr.io/${{ github.repository }}:latest
+            ghcr.io/${{ github.repository }}:${{ github.sha }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max

Dockerfile

@@ -14,13 +14,12 @@ RUN apt-get update && apt-get install -y \
     && rm -rf /var/lib/apt/lists/*
 
 # Install required R packages
-RUN R -e "install.packages(c('ggplot2', 'dplyr', 'tidyr', 'cowplot', 'scales'), repos='http://cran.rstudio.com/')"
+RUN R -e "install.packages(c('ggplot2', 'dplyr', 'tidyr', 'cowplot', 'scales', 'segmented'), repos='http://cran.rstudio.com/')"
 
 # Copy the R script to the working directory
 COPY bedgraph-visualizer.R .
 
 
-
 # Example usage:
 # docker build -t my-r-script .
 # docker run --rm -v $(pwd)/output:/usr/src/app/output my-r-script BAF.bedgraph.gz LRR.bedgraph.gz regions.bed output

README

@@ -0,0 +1,3 @@
+# Example usage:
+# docker build -t my-r-script .
+# docker run --rm -v $(pwd)/output:/usr/src/app/output my-r-script BAF.bedgraph.gz LRR.bedgraph.gz regions.bed output

bedgraph-visualizer.R

@@ -118,17 +118,20 @@ genome_plot <- function() {
 }
 
 # Function to plot specific regions
-region_plot <- function(region_file, padding_percent=0.2) {
+region_plot <- function(region_file, min_padding=600000) {
   # Load region data
   regions <- read.table(region_file, header = FALSE)
   colnames(regions) <- c("Chr", "Start", "End", "Type")
 
   # Iterate over each region and create plots
   for (i in 1:nrow(regions)) {
     region <- regions[i, ]
-    padding = (region$End - region$Start ) * padding_percent
-    padded_start = region$Start - padding / 2
-    padded_end = region$End + padding / 2
+    padding = (region$End - region$Start )
+    if (padding <= min_padding) {
+      padding = min_padding
+    }
+    padded_start = region$Start - padding
+    padded_end = region$End + padding
 
     # Filter BAF and LRR data for the current region
     filtered_baf <- baf_data %>%