pnpnpn/gimsan-py

GIMSAN: motif-finder with biologically realistic and reliable statistical significance analysis

GIMSAN

http://www.cs.cornell.edu/~ppn3/gimsan/

Installation

1. Install required Python libraries:

    sudo pip install -r requirements.txt
   

2. Compile GibbsMarkov and ColumnDependency:

    ./compile_clean.sh
   

Usage Example

1. Set and verify GIMSAN job configuration file conf_examples/test_window_sampling.cfg. Ensure your gimsan_home and r_path directory/path are pointing to the correct location.

2. Submit GIMSAN job using window-sampling:

     ./gimsan_submit.py --conf=conf_examples/test_window_sampling.cfg -v
   

3. Generate results and HTML output for GIMSAN job. If parameter main_output_dir=testout/ is set in configuration file, then run:

     ./gimsan_result.py --dir=testout
   

4. Open HTML file testout/ABF1_YPD_mod/output.html