This repository hosts a PPI-based gene list enrichment tool.
This tool calculates shortest paths between desired two node lists and assesses their statistical significance using hypergeometric tests. Statistical significance is assessed through presence of validated disease-associated genes in calculated paths. Shortest paths were then enriched with KEGG pathways.
You can get this tool with
git clone https://github.com/asyavuz/ppi_dnmt_analysis.git
command.
This tool is tested only on Mac OSX (El Capitan). If you observe any problems, please report it at the Issues section.
Please refer individual websites of required libraries/tools for their installation instructions.
Initially, you need to create the PPI network. You can use BioGrid links file or SIF files.
In order to generate PPI from a BioGrid links file, you may use the following command:
python helperscripts/generate_ppi_from_BioGrid.py -i [BIOGRID_LINKS_FILE_LOCATION]
or for SIF files you can use:
python helperscripts/generate_ppi_from_sif.py -i [SIF_FILE_LOCATION]
For additional parameters of these scripts please type:
python [SCRIPT_NAME] --help
After generation of PPI network, you need to calculate shortest paths. You may run this part using PyPy as it reduces run time significantly.
Please run following command, and find out necessary parameters for your analysis:
python generate_paths.py --help
Lastly, you may enrich calculated shortest paths with analysis script. You can view necessary parameters of this script by
python analyse_shortest_paths.py --help
Please open an issue in this page if you have any questions.
This tool uses the BSD-3 License (see LICENCE).
If you would like to use tool in your publications, please consider citing:
Yavuz, A.S. (2017). Predictive analysis of epigenetic variability (Unpublished doctoral dissertation). Sabanci University, Istanbul, Turkey.