cadd-threshold-app 0.0.4

Shiny-for-Python app for exploring ClinVar distributions across CADD score thresholds

CADD Threshold APP

A Shiny-for-Python web application to explore and compare distributions of ClinVar variants across different CADD PHRED-score thresholds, filter by gene lists or panels, and export per-gene/per-panel or filtered annotation summaries. The app is primarily intended for investigating the score distribution of known pathogenic and benign variants for different CADD PHRED-score thresholds.

This README explains the repository layout, how to run the app locally (pip/conda).

Highlights

• Interactive visualizations of CADD PHRED-score distributions
• Compare distributions across CADD/ClinVar versions and genome builds
• Per-gene filtering (paste a list or upload a file) and exportable summaries
• Per-panel filtering using panels from PanelApp and exportable summaries

Requirements

• Python 3.10+ (3.12 recommended)
• See requirements.txt or environment.yml for full dependencies
• Docker (optional) — a Dockerfile is included for containerized runs

Installation

Data preperation

The underlying data for the CADD-ThresholdApp needs to be downloaded, if the source code is downloaded as a package from bioconda or pip. The data can be downloaded here. The data is also versionized seperately from the packages. You can also preprocess your own data for the website using this Snakemake workflow: https://github.com/kircherlab/CADD_threshold_analysis.

Data overview

• data/ - contains preprocessed tables, panel summaries and metrics used by the app.
  • paneldata/ - CSVs summarizing panels and versions used by the UI
  • panel_metrics/ - generated metrics stored by date/version

Notes:

• Large raw annotation files are typically not tracked in the repository. The app expects prepared/normalized CSV inputs - use https://github.com/kircherlab/CADD_threshold_analysis to regenerate CSV inputs or use the modules/panelapp/ utilities if you need to regenerate panel CSVs from PanelApp.

Pre-compiled packages

Using conda

conda create -n cadd_threshold_app -c bioconda -c conda-forge cadd-threshold-app
conda activate cadd_threshold_app
cadd-threshold-app --data </path/to/data>

Using pip

pip install cadd-threshold-app
cadd-threshold-app --data </path/to/data>

From source

git clone https://github.com/kircherlab/CADD_threshold_app.git
cd CADD_threshold_app
pip install .
cadd-threshold-app --data data

Install as package (editable, recommended for development)

pip install -e .

Run the app

Option A: run via the package entry point

This requires installing the project as a package (e.g. pip install -e .).

cadd-threshold-app --data </path/to/data>

Alternatively to the cli option --data, you can set the CADD_THRESHOLD_APP_DATA_DIR environment variable.

export CADD_THRESHOLD_APP_DATA_DIR=data
cadd-threshold-app

Further CLI options are available to configute host and port - run cadd-threshold-app --help for details.

Option B: run from the repository root. Please set the CADD_THRESHOLD_APP_DATA_DIR environment variable to point to your data directory (e.g. data/ in the repository) before running.

export CADD_THRESHOLD_APP_DATA_DIR=data
python -m shiny run cadd_threshold_app.app:app

Then open http://localhost:8080 in your browser.

Key files and modules

• app.py - Shiny app entrypoint and UI wiring
• server_logic.py - main server-side reactive logic and handlers
• data_loader.py - helpers to load and preprocess annotation tables
• ui_components.py - UI
• modules/ - plotting helpers, utilities and gene-list/panel parsing helpers
  • basic_plot.py, basic_bar_plot.py, compare_basic_plot.py - plotting factories
  • functions_server_helpers.py, read_genes_from_list_or_file_functions.py - utilities
  • panelapp/ - scripts to interact with PanelApp (CSV generation, comparison)

Development notes

• To extend plots: add a factory under modules/ and register it in server logic
• To add data sources: update data_loader.py and ensure column names match the plotting/metric code paths
• Linting/tests: None included by default. Add unit tests for critical data parsing when making larger refactors.

Docker

• The included Dockerfile builds a minimal image running the app on port 8080.

License & contact

• See LICENSE for licensing terms.
• For questions about data sources, interpretation, or contributions, contact the repository maintainers or open an issue.