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RiboDiff: Tool to detect changes in translational efficiency based on ribosome footprinting data
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README.md

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.

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