SOFTWARE: RiboDiff

VERSION

0.2.1

Authors

Yi Zhong, Theofanis Karaletsos, Philipp Drewe, Vipin Sreedharan, David Kuo and Gunnar Raetsch.

DESCRIPTION

RiboDiff is a statistical tool to detect the protein translation efficiency change from ribosome footprint profiling data and RNA-Seq data under two different experimental conditions.

URL

http://bioweb.me/ribodiff

REQUIREMENTS

• Python2 >= 2.6.6 (Python3 is not supported yet.)
• Numpy >= 1.8.0
• Scipy >= 0.13.3
• Matplotlib >= 1.3.0
• Statsmodels >= 0.5.0

These requirements can either be installed individually or as a Python distribution that includes all the required packages. Please find more details at http://www.scipy.org/install.html

INSTALLATION

To install RiboDiff, please refer to INSTALL file in this directory.

CONTENTS

All relevant scripts for RiboDiff are located in the subdirectory src.

• src - main codebase for RiboDiff;

• tests - dataset and script for functional test;

• test-data - test dataset for Galaxy system; (move to your galaxy_root_folder/test-data/) You may need to move the test files into your test-data directory so galaxy can find them. If you want to run the functional tests example as:

  sh run_functional_tests.sh -id ribodiff

• tools - util functions for simulating negative binomial count data.

• scripts - TE.py - the main script to start RiboDiff.

GALAXY

https://galaxy.cbio.mskcc.org/tool_runner?tool_id=ribodiff

DOCUMENTATION

To use RiboDiff, please refer to the instructions in MANUAL in this directory.

LICENSE

RiboDiff is licensed under the GPL version 3 or any later version (cf. LICENSE).

CITE US

If you use RiboDiff in your research you are kindly asked to cite the following publication:

Zhong Y, Karaletsos T, Drewe P, et al. RiboDiff: Detecting Changes of Translation Efficiency from Ribosome Footprints. bioRxiv. doi: 10.1101/017111.