This is a Python 3 port of the Topological Clustering Semantic Similarity (TCSS) algorithm. For any queries please conact the original authors Gary D. Bader [email protected] or Shobhit Jain [email protected].
The original version can be downloaded from http://baderlab.org/Software/TCSS.
Requirements:
- Python 3+
Files provided:
- gene_ontology.obo.txt : Gene Ontology obo file
- gene_association.sgd : SGD annotation file
- *.py : Python files of TCSS implementation
Usage of TCSS implementation in Unix/Linux systems:
Use the following comand to run TCSS.
tcss.py [-options] geneA geneB
or
tcss.py [-options] -i input_file
Example: python tcss.py -i datasets/sgd_data/iea-/positives.sgd.c -o out.txt -c C:2.4 --drop="IEA" --gene=datasets/sgd_data/gene_association.sgd
-options
-i [file name] or --input [=file name] Input file (two genes separted by comma per line)
-o [file name] or --output [=file name] Output file
-c [domain:cutoff] or Domain [C/P/F], cutoff [int/float] in any combination
--topology-cutoff [=domain:cutoff] (default: C:2.4,P:3.5,F:3.3)
--detail Detailed output (default: False)
--gene [=file name] Gene annotation file (default: SGD file provided)
--go [=file name] Gene Ontology (GO) obo file (default: GO file provided)
--drop [=evidence code] GO evidence code not to be used
-h or --help Usage
Note: The program currently works with only SGD gene ids or UniProtKB human ids.