Consensus Active Module Identification - CAMI

Intro | Installation | Description | Usage | LICENSE

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Intro

Installation

  git clone https://gitlab.rrz.uni-hamburg.de/bay2046/systembiologie.git

Description

CAMI has two functions:

• Consensus Prediction: Use different algorithms to find active disease modules in a given PPI-network and combines their results.
• Uses a protein-protein-interaction-network (PPI-network) and a seed list as input Evaluation: Evaluate different tools with respect to the consensus of multiple tools.

Usage

./cami.py [-n] [PPI] [-s] [SEEDS] [-t] [TOOLS] [-id] [IDENTIFIER]

Example

./cami.py -n ./human_annotated_PPIs_brain.txt  -s ./ms_seeds.txt -t robust -id test_run

CAMI flags

    -n or --ppi_network  # Path to a csv file containing the different edges
                         # of the base PPI
    -s or -seeds         # Path to a txt file containing the seeds delimitered
                         # by breakline characters
    -t or --tools        # List of tools that the user wants to use
                         # for prediction. Available tools are
                         # domino, diamond, robust, hotnet.
                         # The default tools are: diamond, domino and robust.
    -w or --tool_weights # List of weights for the tools. If you have
                         # [domino, diamond, robust] as list of tools and
                         # diamonds weight should be twice as high as
                         # the other tools type: 1 2 1
    -c or --consensus    # run the consensus prediction part of cami
    -e or --evaluate     # run the evaluation part of cami
    -o or --output_dir   # path to output directory
    -id or --identifier  # ID for the current excecution of cami.
                         # Defaults to a randomly generated ID
    -tmp or --save_temps # keep temporary files

LICENSE

Released under the GNU General Public License v3.0.