cortexpy

A Python API for manipulating (Mc)Cortex de novo assembly graph and link data

https://github.com/winni2k/cortexpy

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A Python API for manipulating (Mc)Cortex de novo assembly graph and link data

README.rst

Overview of Cortexpy_
=====================

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Cortexpy is a Python package for sequence analysis using linked and colored De Bruijn graphs such as
the ones created by Cortex_ and Mccortex_.
This project aims to mirror many of the features contained in
`CortexJDK `_.

.. _cortexpy: https://github.com/winni2k/cortexpy

Cortexpy also comes with a command-line tool for basic inspection and manipulation of Cortex graphs with and without links.

.. _Cortex: https://github.com/iqbal-lab/cortex
.. _Mccortex: https://github.com/mcveanlab/mccortex

Audience
--------

The audience of cortexpy is researchers working with colored De Bruijn graphs and link information in Cortex_ and Mccortex_ format.


Free software
-------------

Cortexpy is free software; you can redistribute it and/or modify it under the
terms of the Apache License version 2.0.  Contributions are welcome. Please join us on `GitHub `_.


Installation
------------

::

    pip install cortexpy


Documentation
-------------

For more information, please see cortexpy documentation_.

.. _documentation: https://cortexpy.readthedocs.io/en/latest/index.html

Citing cortexpy
---------------

If you use cortexpy in your work, please consider citing:

    Akhter, Shirin, Warren W. Kretzschmar, Veronika Nordal, Nicolas Delhomme, Nathaniel R. Street, Ove Nilsson, Olof Emanuelsson, and Jens F. Sundström. "Integrative analysis of three RNA sequencing methods identifies mutually exclusive exons of MADS-box isoforms during early bud development in *Picea abies*." *Frontiers in Plant Science* 9 (2018). https://doi.org/10.3389/fpls.2018.01625

Bugs
----

This code is maintained by Warren Kretzschmar .
For bugs, please raise a `GitHub issue `_.

Development
-----------

1. Install `conda `_.
2. Download mccortex for testing::

    conda env create -f environment.yml -n my-dev-environment

3. Activate development environment::

    conda activate my-dev-environment

4. Install remaining development tools::

    pip3 install -r requirements.txt


All remaining commands in the development section need to be run in an activated
conda dev environment.



Tests
`````

::

    make test

Deploy new cortexpy version to pypi
```````````````````````````````````

Requires access credentials for pypi.

::

    make deploy

Building the docs
`````````````````

The documentation is automatically built by read-the-docs on push to master.
To build the documentation manually::

    # install sphinx dependencies
    pip install -r docs/requirements.txt

    make docs

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