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P6

Peter's Parse and Processing of Prenatal Particulars via Pandas

A simple, extensible CLI for downloading the Human Phenotype Ontology, parsing genotype/phenotype Excel workbooks, and producing GA4GH Phenopackets as specified here.

Table of Contents

  1. Features
  2. Prerequisites
  3. Installation
  4. Quickstart
  5. CLI Reference
  6. Development & Testing
  7. Contributing
  8. License
  9. Contact

Features

  • Download: fetch the latest or a specific hp.json release from GitHub
  • Parse: autodetect genotype vs phenotype sheets in any Excel workbook
  • Normalize: clean up column names, HPO IDs, timestamps, and data types
  • Generate: emit individual Phenopacket files, one per record (will change the file extension later)

Installation

  1. Clone the repo:

    git clone https://github.com/VarenyaJ/P6.git
cd P6

  2. (Recommended) Create a virtual environment (venv or Conda):

    === Simple Venv setup ===

    python3 -m venv .venv
source .venv/bin/activate

    === or with Conda ===

    conda env create -f requirements/environment.yml -y
conda activate P6

  3. Install via pip:

    python3 -m pip install -r requirements/requirements.txt .

  4. Verify the installation:

    p6 --help

    You should see something like:

    Usage: p6 [OPTIONS] COMMAND [ARGS]...

  P6: Peter's Parse and Processing of Prenatal Particulars via Pandas.

Options:
  --help  Show this message and exit.

Commands:
  download    Download a specific or the latest HPO JSON release into...
  parse-excel Read each sheet, check column order, then: - Identify as a...

Quickstart

Download HPO JSON

Fetch the latest release into tests/data/ (the default directory):

p6 download

After running, you’ll have tests/data/hp.json.

Parse Excel to Phenopackets

With your HPO JSON in place at tests/data/hp.json, run:

p6 parse-excel -e tests/data/Sydney_Python_transformation.xlsx

Resulting phenopacket files will be under:

phenopacket_from_excel/$(date "+%Y-%m-%d_%H-%M-%S")/phenopackets/

Audit Excel Workbooks

Quickly check each sheet in an Excel file for header normalization, sheet classification, and presence of required variant columns.

p6 audit-excel -e tests/data/Sydney_Python_transformation.xlsx

By default you get a table; use -r for a JSON output to the console.

p6 audit-excel -e tests/data/Sydney_Python_transformation.xlsx -r

CLI Reference

p6 download

Usage:

p6 download [OPTIONS]

Options:

    -d, --data-path PATH        where to save HPO JSON (default: tests/data)
    -v, --hpo-version TEXT      exact HPO release tag (e.g. 2025-03-03 or v2025-03-03)
    --help                      Show this help message and exit.

Examples:

Fetch a specific release tag (e.g. v2025-03-03 or 2025-03-03) into tests/data/ (the default directory):

p6 download -v 2025-03-03
p6 download --hpo-version 2025-03-03

Fetch a specific release tag (e.g. v2025-03-03 or 2025-03-03) into a custom directory:

p6 download -d src/P6 -v 2025-03-03
p6 download --data-path src/P6 --hpo-version 2025-03-03

p6 parse-excel

Read an Excel workbook, classify sheets, normalize fields, and emit Phenopacket protobuffers.

Usage: p6 parse-excel [OPTIONS] EXCEL_FILE

Options:

    -e, --excel-path FILE       path to the Excel workbook  [required]
    -hpo, --custom-hpo FILE     path to a custom HPO JSON file (defaults to `tests/data/hp.json`)
    --help                      Show this message and exit.

Example:

Explicitly point at a custom HPO file:

p6 parse-excel -e tests/data/Sydney_Python_transformation.xlsx -hpo src/P6/hp.json

p6 audit-excel

Run a lightweight audit on each sheet in an Excel workbook, reporting header counts, sheet classification, and missing variant‐column checks.

Usage: p6 audit-excel [OPTIONS] EXCEL_FILE

Options:

    -e, --excel-path FILE   path to the Excel workbook  [required]
    -r, --report-json       output audit report as JSON instead of table
    --help                  Show this message and exit.

Development & Testing

Install dev requirements:

python3 -m pip install -r requirements/requirements.txt -r requirements/requirements_test.txt .

This will install P6 along with the dependencies needed for the development.

Run the full test suite:

pytest -q

Lint & type-check (via ruff and built-in assertions):

ruff check .
ruff format .

Contributing

  1. Fork the repo & create a feature branch
  2. Make your changes & add tests
  3. Ensure all tests pass & lint is clean
  4. Submit a pull request against main
  5. Please follow the AGPL-3.0 code of conduct.

License

This project is licensed under the AGPL-3.0. See LICENSE for details.

Contact

Varenya Jain varenyajj@gmail.com GitHub: @VarenyaJ