lunnwa/snowa repository overview

⁠SNOWa Genomic Surveillance Environment

This container provides the standardized data science environment required to run SNOWa, a genomic surveillance pipeline for SARS-CoV-2 wastewater genomic surveillance reporting using Freyja sequencing data results.

docker pull lunnwa/snowa:latest

⁠🔬 Purpose & Use Case

Wastewater genomic sequencing requires specific, pinned data science package versions to ensure reproducible variant tracking and automated public health reporting. This image packages Python 3.10 along with geospatial and visualization libraries to eliminate local dependency conflicts during pipeline execution.

⁠🚀 Pipeline Integration (Intended Workflow Execution)

This container is designed to serve as the automated runtime environment for the SNOWa workflow via Snakemake. Snakemake handles the image download, conversion, and environment management automatically behind the scenes using Singularity.

⁠1. Configure the Workflow

To point the pipeline to this environment, specify the container image within your defaults/config.yaml file:

containerized: "docker://lunnwa/snowa:latest"

⁠2. Execute the Pipeline

Run the workflow from your terminal workspace. The --use-singularity flag tells Snakemake to pull this image, convert it to a Singularity container, and execute the execution steps inside this environment:

snakemake --cores 6 --use-singularity

⁠💻 Standalone Execution (Testing & Debugging)

Because this container acts as the runtime environment for the SNOWa pipeline scripts. For testing with customized scripts, you must mount your local analysis scripts and data paths when running it outside of the Snakemake pipeline.

⁠1. Interactive Shell (Testing & Debugging)

Launch an interactive shell inside the environment to manually test your pipeline scripts or inspect the environment:

docker run -it \
  --name snowa-env-test \
  -v /absolute/path/to/your/scripts:/app \
  -v /absolute/path/to/your/data:/data \
  lunnwa/snowa:latest /bin/bash

(Note: Replace /absolute/path/to/your/... with the real folder locations on your server or computer).

⁠2. Run a Script Directly

Execute an automated SNOWa reporting run directly from your terminal workspace without opening an interactive shell:

docker run --rm \
  -v \$(pwd):/workspace \
  -w /workspace \
  lunnwa/snowa:latest python your_script_name.py

⁠📦 Environment Specifications

The environment is built on Ubuntu 22.04 and pinned to the following core software versions, with additional reporting dependencies included for automated markdown-to-PDF report generation.

⁠🧑‍💻 Maintainer Information

• Maintainer: Steph M Lunn, MPH, MS
• Agency: Washington State Department of Health (DOH)
• Contact Email: [email protected]⁠