https://github.com/kdm9/mpg

Markovian sequence generator
https://github.com/kdm9/mpg

Last synced: 11 days ago
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Markovian sequence generator

• Host: GitHub
• URL: https://github.com/kdm9/mpg
• Owner: kdm9
• License: mit
• Created: 2016-03-05T07:22:54.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2017-04-26T11:41:52.000Z (over 7 years ago)
• Last Synced: 2024-10-28T23:54:56.954Z (18 days ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 104 KB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

        
============================

Markovian Sequence Generator

============================

Generates DNA sequences using a Markov Chain, learned from some reference

sequence(s).

Many thanks to Ben Kaehler for a proof of concept and mathematical assistance.

**Disclaimer**: This is unstable software at the moment. Use with caution.

.. image:: https://travis-ci.org/kdmurray91/mpg.svg?branch=master

    :target: https://travis-ci.org/kdmurray91/mpg

Installation

------------

.. code-block:: shell

    pip3 install mpg

Usage

-----

The script ``mpg`` should have been installed. This learns the transition

probablitlies from sequences (in Fasta format) and generates random sequences

from this Markov chain.

To learn transition probabilities for a 5th-order Markov chain from the

Arabidopsis genome and store them in a file (``ath.h5``):

.. code-block:: shell

    mpg -k 5 -d ath.h5 TAIR_10.fasta

To use these transition probablitlies to generate a sequence of 1000bp:

.. code-block:: shell

    mpg -l 1000 -r ath.h5

To do the above operations at once:

.. code-block:: shell

    mpg -l 1000 -k 5 TAIR_10.fasta