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plotnineSeqSuite: a Python package for visualizing sequence data using ggplot2 style.

Tianze Cao1, Qian Li2, Yuexia Huang3

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

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Summary
This summary is machine-generated.

This study introduces plotnineSeqSuite, a Python package for creating sequence logos and other bioinformatics visualizations. It offers a ggseqlogo-like API, enhancing R-Python programming uniformity for sequence data analysis.

Keywords:
Bioinformatics toolMultiple sequence alignmentSequence logoggplot2plotnine

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Visualization

Background:

  • Visual sequence logos are crucial in bioinformatics tool development.
  • R's ggseqlogo is a popular API, but Python is increasingly used by bioinformaticians.
  • A need exists for Python-based tools mirroring R's visualization capabilities to ease transitions.

Purpose of the Study:

  • To introduce plotnineSeqSuite, a Python package providing a ggseqlogo-like API.
  • To enable programmatic drawing of sequence logos, alignment diagrams, and histograms in Python.
  • To unify bioinformatics visualization programming between R and Python.

Main Methods:

  • Developed plotnineSeqSuite, a Python package utilizing the plotnine library.
  • Implemented a ggseqlogo-like API for sequence visualization.
  • Employed an object-oriented design for drawing layers, allowing for extensibility.

Main Results:

  • plotnineSeqSuite offers a Pythonic alternative to R's ggseqlogo for sequence visualization.
  • The package supports custom letters, color themes, and fonts.
  • It provides a more comprehensive set of supported visualization categories compared to existing tools.

Conclusions:

  • plotnineSeqSuite is the first ggplot2-style package for sequence graph visualization in Python.
  • It improves the consistency of programmatic plotting between R and Python environments.
  • The package offers extensive visualization options and is available on GitHub and PyPI with documentation.