A C++ implementation of the combinatorial entropy optimization (CEO) algorithm. Originial publication: Reva, B., Antipin, Y. & Sander, C. Determinants of protein function revealed by combinatorial entropy optimization. Genome Biol 8, R232 (2007).

Usage

Follow the instructions in src/README.txt to compile the C++ code and place the binary in your $PATH.

To cluster sequences in a multiple sequence alignment (MSA), run the Python script:

python ceo.py [options] msa_file

msa_file: MSA in FASTA format

Options:

--max-col-gap: Maximum fraction of gaps allowed in an MSA column. Default: 0.3. Columns with more gaps are not used for clustering.

-A: Range of the A parameter (begin,end,step). Default: 0.5,0.975,0.025.

--threads: Number of threads to use. Default: 4.