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TFBPShiny

A Shiny web application for exploring transcription factor binding and perturbation data from the Brent Lab yeast collection.


Resource Requirements

This app requires the following minimum resources to run:

  • 4GB storage on disk
  • 8GB RAM (10GB or more is recommended for better performance)

Quick start

If you wish to keep the app separated from your local environment, you should first create a virtual environment. You can do this with venv. cd to the directory where you want the virtual environment to be created, and run:

python -m venv tfbpshiny_env
source tfbpshiny_env/bin/activate

Install

python -m pip install tfbpshiny

Run the app:

This will download the necessary datasets from huggingface into a cache directory that is created in your current working directory. By default, it is called ./tfbpshiny_hf_cache. When you run the app again, if you launch it from the same location it will verify that the cache is up to date, and use it, without re-downloading. You can also specify a custom cache directory with --cache-dir.

python -m tfbpshiny launch

To install the latest development version from GitHub, use:

python -m pip install git+https://github.com/BrentLab/tfbpshiny@dev

For production deployment (EC2/Docker) and shinyapps.io deployment instructions, see docs/development.md.


Contributing

Setup

git clone https://github.com/BrentLab/tfbpshiny.git
cd tfbpshiny
poetry install
pre-commit install
# First-time Playwright setup (required for E2E tests)
poetry run playwright install chromium

Plotly JS bundle

The app loads Plotly from a local bundle (tfbpshiny/www/plotly-3.5.0.min.js) rather than a CDN to avoid race conditions when multiple outputs initialize simultaneously. This file is gitignored due to its size (~4.8 MB). After cloning, download it once:

curl -fsSL https://cdn.plot.ly/plotly-3.5.0.min.js \
    -o tfbpshiny/www/plotly-3.5.0.min.js

If the plotly Python package is upgraded, check the new JS version it expects:

python -c "
import re, plotly.graph_objects as go
from plotly.io import to_html
m = re.search(r'plotly-([\d.]+)\.min\.js', to_html(go.Figure(), include_plotlyjs='cdn'))
print(m.group(0))
"

Then download the matching version and update the src in tfbpshiny/app.py.

Environment variables

Create a .env file in the repo root to override defaults:

# Optional — only needed for private HuggingFace datasets
HF_TOKEN=<your_huggingface_token>

# Optional — override the VirtualDB config path
VIRTUALDB_CONFIG=/path/to/custom_config.yaml

Running the app

poetry run python -m tfbpshiny --log-level DEBUG launch \
    --port 8010 --host 127.0.0.1 --debug

Running tests

poetry run pytest tests/unit/      # unit tests
poetry run pytest tests/e2e/       # end-to-end
poetry run pytest                   # all tests

Code quality

pre-commit run --all-files

Branching

  1. Switch to dev: git switch dev
  2. Branch from devnot main: git switch -c my-feature
  3. Keep branches small and focused to make review easier
  4. Rebase onto dev periodically: git rebase dev
  5. When ready, open a pull request targeting the BrentLab dev branch — not main

Release files for tfbpshiny 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Total release size:700.1 kB

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