An adaptable python package for Gene Ontology semantic similarity based functional analysis
 Maintainer: Gaston K. Mazandu <gmazandu at {cbio.uct.ac.za, gmail.com}, kuzamunu at aims.ac.za>
 Contributors: Gaston K. Mazandu1, 2, Emile R. Chimusa1, Mamana Mbiyavanga1, 2 and Nicola J. Mulder1

 

(1) Computational Biology (CBIO) Group, Department of integrative Biomedical Sciences
    Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town (UCT), Observatory 7925, South Africa

 

(2) African Institute for Mathematical Sciences (AIMS), South Africa and Ghana
    Melrose Road, Muizenberg 7945 and Biriwa, LG 197 Cape Coast

 


The A-DaGO-Fun Package

A python library that provides a comprehensive and customized set of Gene Ontology (GO) based functional analysis tools that exploit the biological knowledge that GO offers in describing genes or groups of genes through the use of GO semantic similarity measures for biological knowledge discovery.

This package implements 11 GO term semantic similarity approaches (annotation-based: Resnik, XGraSM-Resnik, Nunivers, XGraSM-Nunivers, Lin, XGraSM-Lin, Relevance and Li et al., and topology-based: Wang et al., Zhang et al. and GO-universal) and 101 different functional similarity measures between gene products based on their GO annotations. Moreover, it includes several biological applications related to GO semantic similarity scores, including the retrieval of genes based on their GO annotations, the clustering of functionally related genes within a set, and term enrichment analysis.


Protein identification (proteinfit)

Term enrichment analysis (gossfeat)

Functional Classification (proteinfct)

Installation

To install this package, go to the dagofun directory and type the following command line:

python setup.py install --user

It is worth mentioning that A-DaGO-Fun is a portable python package and can be used without installing the whole package. You only need to be on a directory containing dagofun folder, which is a python library of A-DaGO-Fun.

Documentation

To view documentation for the version of this package installed in your system, go to the dagofun directory and type the following command line:

python setup.py --long-description

Refer to the PDF version of the documentation below for more information on package installation and administration, as well as information on different IC models, term semantic similarity approaches and functional similarity measures.

 

TXT Show Library Source A-DaGO-Fun
PDF   Reference Manual

Details

Description Computing GO-based semantic similarity scores and includes several other biological applications related to GO semantic similarity measures
Version 15.1
Applications Term Information Content value and semantic similarity score retrieval, Protein clustering, Protein identification, Term enrichment analysis
Depends Python, but not tested on the version less than 2.7.3
License GPL (>= 2)
Imports scipy, matplotlib, networkx
SystemRequirements OS Independent, but tested only on Linux (Ubuntu)

Package Archives

Follow Installation instructions and read the package PDF and txt documentation files to optimally use this package in your python session.

Package Source dagofun.tar.gz
Browse/checkout web-tool DaGO-Fun
Package site visits' Report

Functions and data versions»

The main functions in the A-DaGO-Fun package are:

  • getTermFeatures, termsim and funcsim
  • proteinfit, gossfeat and proteinfct

Data version for the A-DaGO-Fun package:

Important notes on the DaGO-Fun web-tool:


DaGO-Fun website visitors»



Mailing Lists»

An appropriate DaGO-Fun forum is still to be implemented, for now, any problem accounted when using this tool or comments should be forwarded by email to the DaGO-Fun team:

 Acknowledgements

Any work dependent on open-source software owes debt to those who developed these tools. The authors thank everyone involved with free software, from the core developers to those who contributed to the documentation. Many thanks to the authors of the freely available libraries for making this work possible. This work received no specific funding.

Report a bug  |  Questions or Suggestions    |   Terms of Use   |   DaGO-Fun web-tool   |   Copyright © June 2015. All rights reserved  |  01-06-2015