MIRIPVIR25 🦠🧫

Multiple Infection Role in Plant Virus Infection Risk

Project overview

MIRIPVIR25 explores virus–bacteria interactions in plant-associated metatranscriptomes. To our knowledge, this is a pioneering effort in the field of environmental microbiology. The repository contains data and analysis notebooks.

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Table of contents

• Quick start ✅
• Prerequisites 🔧
• Install & run (using uv) ⚙️
• Repository structure 📁
• Running analyses & docs 📊
• Tests & quality checks ✅
• License & contact 📜

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Quick start

1. Install the uv package manager (recommended via pipx) and use it to install dependencies (see below).

2. Clone the repo:

   git clone https://github.com/wilkinsonlab/miripvir25.git
   cd miripvir25

3. Run the analysis or serve docs (examples below).

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Prerequisites

• macOS / Linux / WSL (Linux)
• Python 3.10+ recommended
• git, make, and basic Unix tools
• uv (https://docs.astral.sh/uv/)

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Install & run (using uv)

Install uv:

Please see the official documentation and installation instructions at: https://docs.astral.sh/uv/

Install project dependencies with uv:

# from project root
uv install         # installs dependencies defined in `pyproject.toml`

Install manually daforfer

uv pip install git+https://github.com/brunocuevas/daforfer

Run common commands through uv (delegates to the project's environment):

# Serve the docs locally
uv run mkdocs serve
# Run notebooks or a Jupyter server
uv run jupyter lab

Notes:

• If you don't have uv available, you can fall back to python -m pip install -e . or use the provided environment.yml to create a conda environment.

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Repository structure

Top-level layout (selected):

• analysis/ — Jupyter notebooks and analysis scripts
• data/ — reference files and genomes
• docs/ — MkDocs documentation and site content
• pipelines/ — reproducible pipelines (e.g., b2s)
• results/ — pipeline output and reports
• scripts/ — helper scripts and utilities
• src/ — source code and modules
• test/ — tests and QA
• pyproject.toml, environment.yml, setup.cfg — project metadata and dependency specs

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Running analyses & docs

• Analysis notebooks: open with uv run jupyter lab and run notebooks in analysis/.
• Pipelines: many pipelines include a run.sh or README in their folder (e.g., analysis/run.sh). Follow the comments in those scripts.
• Docs: to preview documentation locally:

uv run mkdocs serve
# open http://127.0.0.1:8000 in your browser

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Tests & quality checks

Run tests and linters via uv:

# run tests using Python's builtin unittest via uv
uv run python -m unittest discover -v

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License & contact

See the LICENCE.md file in the repository for license details. For questions, open an issue or contact the maintainers listed in pyproject.toml.

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