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pandasPGS: a Python package for easy retrieval of Polygenic Score Catalog data.

Zheyu Zhang1, Jintong Zhou1, Tianze Cao1

  • 1School of Mathematics, Hangzhou Normal University, Hangzhou, Zhejiang, China.

Peerj
|February 17, 2025
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Summary

A new Python package, pandasPGS, simplifies accessing and analyzing Polygenic Score (PGS) Catalog data. This tool streamlines research by eliminating the need to learn complex REST APIs, making polygenic risk score integration easier.

Keywords:
Data frameDatabaseGWASPGSPython

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • The Polygenic Score (PGS) Catalog is a public database containing over 5,000 polygenic risk scores for 656 traits.
  • Accessing PGS Catalog data requires researchers to interact with its REST API, demanding significant time for learning and custom client implementation.
  • A lack of language-specific data clients hinders seamless integration of PGS data into research workflows.

Purpose of the Study:

  • To introduce pandasPGS, a Python package designed for programmatic access to the PGS Catalog.
  • To simplify the process of retrieving and analyzing polygenic risk score data for researchers.
  • To reduce the technical barrier for researchers utilizing PGS Catalog resources.

Main Methods:

  • Developed pandasPGS, a Python package providing an intuitive interface for PGS Catalog data retrieval.
  • Implemented functions that automatically handle URL selection, data requests, and pagination merging.
  • Integrated data pre-processing capabilities to convert retrieved data into hierarchical pandas.DataFrame objects.

Main Results:

  • pandasPGS offers researchers direct programmatic access to the PGS Catalog.
  • The package automates data retrieval and merging, significantly reducing the effort required to obtain polygenic risk score data.
  • Converted data into user-friendly pandas DataFrames, facilitating downstream analysis.

Conclusions:

  • pandasPGS effectively alleviates the time investment required for researchers to learn and utilize the PGS Catalog REST API.
  • The package enhances the accessibility and usability of polygenic risk score data for genetic research.
  • Source code and documentation are publicly available to support adoption and further development.