Framework for creating and analyzing genotype networks from data.
Project description
Genonets
This package provides a high level interface for construction and analysis of genotype networks from data. Also, this is the Python package used by the Genonets Server.
Documentation, including tutorials and API documentation, is available here.
New in version 1.1.10
New feature: If the EPISTASIS
analysis is requested, the Genotype_set_measures.txt
file now contains an additional
column titled Epistasis squares
. Data format for the new column and other detail are available
here.
New in version 1.1.9
Bug fix: In light of the issue reported here, the algorithm for identification of peaks has been revised, as well as thoroughly validated and tested.
New in version 1.1.8
Bug fix: In certain cases, the computation of peaks would result in two or more peaks that share one or more genotypes. This behavior was incorrect, and has therefore been fixed. The corresponding issue is reported here.
New in version 1.1.7
Performance optimization: The code for computation of peaks has been optimized so that it runs significantly faster than the previous version. The changes made only affect performance; the algorithm remains the same. The corresponding issue is reported here.
New in version 1.1.6
Enhancement: The order in which genotype set names appear in the result file Genotype_set_ovelrap.txt
, is now the
same order in which genotype set names appear in the input file. The corresponding issue is reported
here.
New in version 1.1.5
Bug fix: The fix affects the results of Robustness analysis; only when Genonets is used with -rc
or
--use_reverse_complements
options. The impact of this change is higher on genotype level results, but
minimal on genotype set level results. The details of the issue can be found
here.
New in version 1.1.3
Bug fix: The fix affects the results of Evolvability, Accessibility, Neighbor abundance, Diversity index, and Overlap
analyses, only when Genonets is used with -rc
or --use_reverse_complements
options. The impact of this change is
higher on genotype level results, but minimal on genotype set level results. The details of the issue can be found
here.
New in version 1.1.0
The public interface in genonets.genonets_interface.Genonets
has been changed, i.e., several method signatures
used in the previous versions are no longer valid. Please see the API documentation
here.
New in version 1.0.7
- An optional command line argument,
-v
or--verbose
has been introduced. This enables the verbose mode. When used with python-u
flag, detailed progress information is printed to the standard output. - A new analysis type
PATHS_RATIOS
has been added. It enables the computation of ratio of "accessible mutational paths" to "all shortest mutational paths" for a given distance from summit. - An optional command line argument,
-rc
or--use_reverse_complements
has been introduced. This option can only be used with alphabet type 'DNA'. If this option is given, in addition to the genotypes, reverse complements of the genotypes are also considered during genotype network creation, as well as during 'Evolvability', 'Accessibility', 'Neighbor abundance', and 'Diversity index' analysis types.
Installation
Linux (tested on Ubuntu 14.04 LTS and above)
Using pip
,
pip install genonets
In case you get a 'permission' related error, try the following:
sudo pip install genonets
You can also install Genonets directly from the source package.
python setup.py install
Again, in case you run into permission related errors,
sudo python setup.py install
When trying to install genonets on a machine with Ubuntu 14.04 LTS
that does not already have the required version of
python-igraph
installed, pip
sometimes fails to install the C core of igraph. If that happens, follow these steps:
sudo apt-get install build-essential
sudo apt-get python-dev
sudo apt-get install libxml2-dev
sudo apt-get install libz-dev
sudo pip uninstall genonets
- Finally,
sudo pip install genonets
Mac OS X El Capitan
We highly recommend using virtualenv
, or better yet, Anaconda
, for installation on Mac OS X El Capitan.
In case you do not already have virtualenv
installed on your system, use the following command to install
virtualenv
:
pip install virtualenv
In the directory of your choice, create a virtual environment. In the following example, we will create a virtual
environment called venv_genonets
:
virtualenv venv_genonnets
Now, activate venv_genonets
as follows:
source venv_genonets/bin/activate
You are now ready to install Genonets. Use the following command:
pip install genonets
Note: Every time you need to use genonets
, you will have to activate the corresponding virtual environment.
Windows
Instructions for Windows are basically the same, except in certain cases installation of dependencies fails. If that happens, follow these steps:
- Download the 'whl' files for
numpy
andpython-igraph
from http://www.lfd.uci.edu/~gohlke/pythonlibs/. E.g.,numpy-1.10.2+mkl-cp27-none-win32.whl
python_igraph-0.7.1.post6-cp27-none-win32.whl
pip install python_igraph-0.7.1.post6-cp27-none-win32.whl
pip install numpy-1.10.2+mkl-cp27-none-win32.whl
- And finally,
pip install genonets
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