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How can I contribute to RNAlysis?

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions

Report Bugs

Report bugs at https://github.com/GuyTeichman/rnalysis/issues.

If you are reporting a bug, please include:

  • Your operating system name and version.
  • Any details about your local setup that might be helpful in troubleshooting.
  • Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with "bug" and "help wanted" is open to whoever wants to implement it.

Write Documentation

RNAlysis could always use more documentation, whether as part of the official RNAlysis docs, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

The best way to send feedback is to file an issue at https://github.com/GuyTeichman/rnalysis/issues.

If you are proposing a feature:

  • Explain in detail how it would work.
  • Keep the scope as narrow as possible, to make it easier to implement.
  • Remember that this is a volunteer-driven project, and that contributions are welcome :)

Implement Features

You are welcome to implement new features that you think would be useful! If you are looking for ideas, check out the Ideas/To-Do list below:

Ideas/To-Do

This is a rather unsorted list of features that would be nice to have, of things that could be improved in the source code, and of possible algorithmic improvements:

  • Interactive scatter plots (for example - click on a point to show/hide it's gene/sample name)
  • Implement the GSEA single-list enrichment algorithm
  • Accept per-gene scaling factors in addition to per-sample scaling factors
  • Distplot for count matrices
  • Support for single-cell transcriptomics analysis
  • Support for ATAC-seq analysis
  • Generate sashimi plots
  • Generate genome browser-like plots
  • Merge tables row/column-wise
  • Support for additional formats of customized annotations
  • Correlation plots
  • Rank-sum test comparing data from two different columns/tables

RNAlysis Design Philosophy

As a guiding priniple for future development of RNAlysis, see this short list of the general design principle RNAlysis should follow:

  • Universality - RNAlysis should be usable on most computers. This means new features should be supported by commonly-used operating systems (Windows, Linux, MacOS) and currently supported Python versions. In the best case scenario, users who open RNAlysis should never ask themselves "which of these functions/modules are supported by my operating system?"
  • Graphical and Programmatic support - The majority of RNAlysis features should be usable both in the Graphical User Interface, and in Python scripts.
  • Customization and clarity - Functions and algorithms implemented in RNAlysis should give user a high degree of control over the function/algorithm parameters. This serves two purposes: firstly, it allows more advanced users to modify analysis parameters to suit their needs. Second, and perhaps most importantly, specifying and documenting all possible analysis parameters provides a high degree of transparency. Knowing exactly what parameters can be changed, and what are the default values, makes accurate and transparent reporting of analysis much easier. For example, when running GO enrichment, users can know and report exactly how the GO annotations are fetched, filtered, and annotated, which statistical test is used for analysis, etc.

Get Started!

Ready to contribute? Here's how to set up rnalysis for local development.

  1. Fork the rnalysis repo on GitHub.

  2. Clone your fork locally:

    $ git clone git@github.com:your_name_here/rnalysis.git

  3. Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:

    $ mkvirtualenv rnalysis
$ cd rnalysis/
$ python setup.py develop

  4. Create a branch for local development:

    $ git checkout -b name-of-your-bugfix-or-feature

    Now you can make your changes locally.

  5. When you're done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:

    $ flake8 rnalysis tests
$ python setup.py test or py.test
$ tox

    To get flake8 and tox, just pip install them into your virtualenv.

  6. Commit your changes and push your branch to GitHub:

    $ git add .
$ git commit -m "Your detailed description of your changes."
$ git push origin name-of-your-bugfix-or-feature

  7. Submit a pull request through the GitHub website.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

  1. The pull request should include tests.
  2. If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
  3. The pull request should work for Python versions 3.7 - 3.10, and for PyPy. Check https://coveralls.io/github/GuyTeichman/RNAlysis and make sure that the tests pass for all supported Python versions.

Tips

To run a subset of tests:

$ py.test tests.test_rnalysis

Deploying

A reminder for the maintainers on how to deploy. Make sure all your changes are committed (including an entry in HISTORY.rst). Then run:

$ bumpversion patch # possible: major / minor / patch
$ git push
$ git push --tags

Travis will then deploy to PyPI if tests pass.