Skip to content

marco-mariotti/pyranges

 
 

Repository files navigation

pyranges

Coverage Status hypothesis tested PyPI version MIT PyPI - Python Version install with bioconda

Introduction

PyRanges is a Python library specifically designed for efficient and intuitive manipulation of genomics data, particularly genomic intervals (like genes, genomic features, or reads). The library is optimized for fast querying and manipulation of genomic annotations.

"Finally ... This was what Python badly needed for years." - Heng Li

Documentation

The pyranges documentation, including installation instructions, API, tutorial, and how-to-pages, is available at https://pyranges.readthedocs.io/

Features

  • fast
  • memory-efficient
  • featureful
  • pythonic/pandastic
  • supports chaining with a terse syntax
  • uses Pandas DataFrames, so the whole Python data science stack works on PyRanges

Paper/Cite

Stovner EB, Sætrom P (2020) PyRanges: efficient comparison of genomic intervals in Python. Bioinformatics 36(3):918-919 http://dx.doi.org/10.1093/bioinformatics/btz615

Supporting pyranges

  • most importantly, cite pyranges if you use it. It is the main metric funding sources care about.
  • use pyranges in Stack Overflow/biostars questions and answers
  • star the repo (possibly important for github visibility and as a proxy for project popularity)
  • if you are a business using pyranges, please give to one of the charities listed at https://www.givewell.org/

Asking for help

If you encounter bugs, or the documentation is not enough a cannot accomplish a specific task of interest, or if you'd like new features implemented, open an Issue at github: https://github.com/pyranges/pyranges/issues

Contributing to pyranges

Pyranges accepts code contributions in form of pull request. For details, visit https://pyranges.readthedocs.io/developer_guide.html

About

Performant Pythonic GenomicRanges

Resources

License

Code of conduct

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 99.9%
  • Other 0.1%