Metadata-Version: 1.0
Name: caspo
Version: 1.0
Summary: Learning of Protein Signaling Logic Models powered by BioASP and CellNOptR
Home-page: http://pypi.python.org/pypi/caspo/
Author: Sven Thiele, Santiago Videla
Author-email: sthiele@irisa.fr, santiago.videla@irisa.fr
License: LICENSE.txt
Description: ==========================
        caspo :- BioASP, CellNOpt.
        ==========================
        
        caspo combines BioASP_ and CellNOpt_ to provide an easy to use software for learning Protein Signaling Logic Models from a Prior Knowledge Network in `.sif format`_ and a phospho-proteomics dataset in `MIDAS format`_.
        
        .. _BioASP: http://www.cs.uni-potsdam.de/~sthiele/bioasp/
        .. _CellNOpt: http://www.ebi.ac.uk/saezrodriguez/cno/
        .. _`.sif format`: http://wiki.cytoscape.org/Cytoscape_User_Manual/Network_Formats
        .. _`MIDAS format`: http://www.ebi.ac.uk/saezrodriguez/cno/doc/cnodocs/midas.html
        
        Installation
        ============
        
        You can install caspo by running::
        
        	$ pip install caspo
        
        caspo will try to install the R_ package CellNOpt_ (R_ must be already installed). Note that you may need root access for this. Otherwise, you can install CellNOpt_ manually from the R_ console and use a virtualenv_ to install caspo.
        
        .. _R: http://www.r-project.org/
        .. _virtualenv: http://pypi.python.org/pypi/virtualenv
        
        Usage
        =====
        
        Typical usage is::
        	
        	$ caspo.py pkn.sif midas.csv
        	
        For more options you can ask for help as follows::
        
        	$ caspo.py --help
        	Usage: caspo.py [options] pkn.sif midas.csv
        
        	Options:
        	  -h, --help           show this help message and exit
        	  -t T, --tolerance=T  Suboptimal enumeration tolerance (Default to 0)
        	  -p P, --discrete=P   Discretization range exponent: 10^P (Default to 2)
        	  -q Q, --alpha=Q      Size penalty exponent 1/10^Q (Default to 5)
        	  -g, --gtts           Compute Global Truth Tables (Default to False). This
        	                       could take some time for many models.
        	  -o O, --outdir=O     Output directory path (Default to current directory)
        
        Output
        ======
        
        By default, the output of caspo will be 4 comma-separated-values files::
        	- models.csv: Matrix representation of logic models
        	- frequencies.csv: Frequencies of hyperedges occurrence
        	- exclusives.csv: Mutual exclusives hyperedges with their corresponding frequencies
        	- inclusives.csv: Mutual inclusives hyperedges with their corresponding frequencies
        	
        When using the -g option, caspo will also output::
        	- gtt_stats.csv: Basic cluster analysis.
        	- gtt-%i.csv: Explicit computation of each Global Truth Table
        	
Platform: UNKNOWN
