Quickstart

To demonstrate the general way of working with cmonkey-python, we are running through a quick example. It is assumed that the source code is checked out and the prerequisites are all installed and in place. The example was tested on a Linux-based system and should run on a Mac OS X system without modifications.

Included in the source code repository is a small data set for Halobacterium salinarum, which completes in comparatively short time. We will use this data set to generate clusters and a web-based report.

On the command line, we enter the following commands:

    cd <your cmonkey-python directory>
    ./run_cmonkey.sh --ratios halo_ratios5.tsv --organism hal

The clustering application will now run with its default settings and automatically download the auxiliary data it needs from the web. Please ensure that you have a working internet connection. On our test system (Intel i7, 8 GB RAM), this data set finishes in about 1 hour.

cMonkey/Python comes with a monitoring application, which automatically reads the output data and generates statistics about the run currently in progress.

    cd <your cmonkey-python directory>/cluster_viewer
    play
    run

The monitoring application will be started and can be viewed by opening a web browser and entering the address http://localhost:9000.

After the run is finished, the results will be available in the directory your cmonkey-python directory/out path, which contains among other files contains the important result files:

• ratios.tsv.gz - the normalized input matrix
• cmonkey_run.db - the results of the cmonkey run, stored in sqlite3 format

These formats were selected for easier data interchange.