caspo 1.3

Learning Boolean logic models of protein signaling networks powered by PyASP and CellNOptR

caspo combines PyASP and CellNOpt to provide an easy to use software for learning Boolean logic models of protein signaling networks from a prior knowledge network in .sif format and a phospho-proteomics dataset in MIDAS format.

Installation

You can install caspo by running:

$ pip install caspo

Note that you may need root (sudo) access for this. Otherwise, you can use a virtualenv. Before using caspo make sure that R is already installed. The first time you run caspo, CellNOptR will be downloaded and installed in your R environment.

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 [-h] [--version] [--fit F] [--size S] [--discrete D] [--gtts]
                [--cross N K] [--out O]
                pkn midas

positional arguments:
  pkn           Prior knowledge network in SIF format
  midas         Experimental dataset in MIDAS file

optional arguments:
  -h, --help    show this help message and exit
  --version     show program's version number and exit
  --fit F       suboptimal enumeration tolerance (Default to 0)
  --size S      suboptimal size enumeration tolerance (Default to 0). Combined
                with --fit could lead to a huge number of models
  --discrete D  discretization over [0,D] (Default to 100)
  --gtts        compute Global Truth Tables (Default to False). This could
                take some time for many models.
  --cross N K   compute N random K-fold cross validation
  --out O       output directory path (Default to current directory)

Samples

Sample files are available for the prior knowledge network and the phospho-proteomics dataset

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

• exclusive.csv: Mutual exclusives hyperedges with their corresponding frequencies

• inclusive.csv: Mutual inclusives hyperedges with their corresponding frequencies

When using the –gtts option, caspo will also output:

• gtts_stats.csv: Basic cluster analysis.

• gtt-%i.csv: Explicit computation of each Global Truth Table

When using the –cross N K option, caspo will also output:

• cross_validation_%i.csv: K-fold cross validation report for each of the N runs

1.3 (2013-03-08)

• OO refactoring

• Replace deprecated optparse with argparse

• Remove short options

• Implements k-fold cross validation

• Adds size tolerance as an option

• Sphinx docs

1.2 (2013-02-05)

• Depends on PyASP instead of BioASP

• Package the full ASP encoding

• Implements old BioASP’s functionality

• Upgrade dependency on cellnopt.wrapper to 1.0.5

1.1 (2012-12-20)

• Removes CellNOpt installation relying on cellnopt.wrapper

1.0 (2012-12-03)

• Initial release