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RiboDiff: Tool to detect changes in translational efficiency based on ribosome footprinting data
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Yi Zhong, Theofanis Karaletsos, Philipp Drewe, Vipin Sreedharan, David Kuo and Gunnar Raetsch.


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.



  • 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


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


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

  • scripts - - the main script to start RiboDiff.



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


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


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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