###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
###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.