Metadata-Version: 2.0
Name: ddrage
Version: 1.2.2
Summary: Simulator for ddRADseq (double digest restriction site associdated DNA squencing) datasets. Generates reads (FASTQ format) that can be analyzed and validated using a ground truth file (YAML).
Home-page: https://bitbucket.org/genomeinformatics/rage
Author: Henning Timm
Author-email: henning.timm@uni-due.de
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Dist: matplotlib
Requires-Dist: numba
Requires-Dist: numpy
Requires-Dist: pyyaml
Requires-Dist: scipy
Provides-Extra: BBD-visualization
Requires-Dist: bokeh (>=0.12.4); extra == 'BBD-visualization'
Provides-Extra: documentation
Requires-Dist: sphinx (>=1.5.0); extra == 'documentation'
Requires-Dist: sphinx-rtd-theme; extra == 'documentation'

RAGE - ddRAD Data Generator
============================

RAGE (ddRAD Data Generator) is a software to simulate double digest restriction site associated DNA sequencing reads.
The generated data sets can be used to test ddRAD analysis tools and validate their results.

The documentation, including a tutorial, can be found `here <https://ddrage.readthedocs.io/>`_.
The code is hosted on `bitbucket`_, `PyPI`_, and `bioconda`_.

.. _bitbucket: https://bitbucket.org/genomeinformatics/rage
.. _PyPI: https://pypi.python.org/pypi/ddrage/
.. _bioconda: https://bioconda.github.io/recipes/ddrage/README.html

System Requirements
~~~~~~~~~~~~~~~~~~~

- python >= 3.5
- numba
- numpy
- matplotlib
- pyyaml
- scipy


For the docs:

- sphinx
- sphinx_rtd_theme

For parameter visualization:

- bokeh


Installation
~~~~~~~~~~~~

We recommend the installation using conda:

.. code-block:: shell

   $ conda create -c bioconda -n rage  python rage
   $ source activate rage

Alternatively, you can download the source code from `bitbucket`_ and install it using the setup script:

.. code-block:: shell

   $ git clone https://bitbucket.org/genomeinformatics/rage.git
   $ cd rage
   /rage$ python setup.py install

In this case you have to install the requirements listed above.



Usage
~~~~~

To simulate a ddRAD data set, call rage from the command line:

.. code-block:: shell

   $ rage

you can specify parameters to change data set parameters such as number of individuals (``-n``), nr of loci (``-l``), and coverage (``--coverage``):

.. code-block:: shell

   $ rage -n 6 -l 10000 --coverage 30

This creates a data set with reads from 6 individuals at 10000 loci with an expected coverage of 30.

A more detailed tutorial can be found `on readthedocs <https://ddrage.readthedocs.io/en/latest/getting-started/>`_.


