This Docker build combines R and Python environments in a single container based on miniforge3. The container includes:

Python Environment (base):

• Jupyter notebook server
• Data science packages: pandas, matplotlib, seaborn, biopython, pysam, regex, altair, openpyxl
• Workflow management: snakemake-minimal

R Environment:

• Tidyverse ecosystem: r-tidyverse, r-janitor, r-glue, r-devtools
• Plotting: r-plotrix, r-ggrepel, r-ggridges, r-ggpubr
• Bioconductor packages: plyranges, flowcore, BSgenome, org.hs.eg.db, DESeq2, ggbio
• IRkernel for Jupyter integration

cirro Environment (v2.2.0+):

• Python 3.10 with pip
• cirro package for cloud data platform integration

Additional Tools:

• GitHub CLI and AWS CLI
• DVC and DVC-S3 for data versioning
• Helvetica and DejaVu fonts for plotting

docker run --rm --user $(id -u):$(id -g) \
  -v /home/$USER:/home/$USER -w "$(pwd)" \
  ghcr.io/rasilab/r_python:2.4.2 python script.py

The --user flag ensures output files are owned by the calling user instead of root.

singularity exec -B /home/$USER r_python_2.4.2.sif python script.py

Singularity automatically maps the host user.

See Dockerfile for complete build details.