snps2vcf

snps2vcf is a tool for converting direct-to-consumer microarray results into VCF files using the snps package.

usage

To use, pipe input into the process and pipe the output somewhere. e.g.

python -m snps2vcf < input.txt.gz > output.vcf

development

# Create virtual environment
python3 -m venv venv
# Activate virtual environment
source venv/bin/activate

# first install pip tools
pip install pip-tools
# Install exact requirements
pip-sync requirements.txt requirements-dev.txt
# Install editable snps2vcf with development extras
pip install -e '.[dev]'

# before making any code changes
# Run tests
pytest --cov-report=html --cov=snps2vcf tests
# Linting
ruff check --fix
# Formatting
ruff format
# Type checking
mypy --strict snps2vcf

# after making any dependency changes
# Freeze dependencies
pip-compile
# Freeze dev dependencies
pip-compile requirements-dev.in
# then run pip-sync again to install them!

Global git ignores per https://help.github.com/en/github/using-git/ignoring-files#configuring-ignored-files-for-all-repositories-on-your-computer

For release to PyPI see https://packaging.python.org/tutorials/packaging-projects/

To add a new development dependency, add to requirements-dev.in then run pip-compile requirements-dev.in

To add a new dependency, add to requirements.in then run pip-compile

docker

To build this container, use the following command:

docker/build.sh

Input and output to the container can be passed either via stdin / stdout or by mapping the local filesystem to the container and passing file arguments. Both options create the output file (output.vcf) in the current directory.

Using stdin / stdout

docker run --rm -i snps2vcf sh run.sh < input.txt.gz > output.vcf

Using File Arguments

docker run --rm -v $(pwd)/input.txt.gz:/app/input.txt.gz -v $(pwd):/app/output_dir snps2vcf sh run.sh /app/input.txt.gz /app/output_dir/output.vcf

acknowledgements

snps2vcf incorporates code and concepts generated with the assistance of OpenAI's ChatGPT. ✨