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CyGenexpi

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Martin Černý edited this page Jan 9, 2017 · 4 revisions

CyGenexpi is a Cytoscape plugin for validating/inferring genetic networks from time series expression data. It is based on a ordinary differential equation (ODE) model of gene regulation published in Vohradský J., 2001.

Installation

Cytoscape and by extension CyGenexpi require 64bit system with Java 1.8 or later, 64bit.

  • Method 1: Via Cytoscape. If you already have Cytoscape (version 3.4+) you can get CyGenexpi from within Cytoscape through Apps -> App Manager, and search for "CyGenexpi".

  • Method 2: Standalone package. You can also download a complete package of Cytoscape with CyGenexpi preinstalled.

    For the archive distributions, simply unpack the file and run cytoscape.bat (Win) or cytoscape.sh (Unix).

Usage

Is best shown by an Example.

The general process followed with Genexpi is:

  1. Start with a network of putative regulations either obtained from database mining or experiments, (for network inference, this may be a complete graph).
  2. The time-course data are smoothed to provide a continuous curve, we had best results with either polynomial spline or linear kernel estimator.
  3. Remove genes whose expression does not change significantly throughout the whole time-course.
  4. Remove genes that could be modelled with 0 regulators (e.g. whose expression could be explained by mRNA synthesis being constant throughout the whole time-course).
  5. Optional: Human inspection of the results of steps 2&3, possibly overriding the algorithm’s decisions.
  6. Finding best parameters of the ODE model for each gene-regulator pair. The fitted models are then classified into good and bad fits. Good fits indicate that the regulation is plausible, while bad fits show that the regulation either does not take place or involves additional regulators.
  7. Optional: Human inspection of the fits, possibly overriding the algorithm’s classification.

CyGenexpi handles time series with the help of the CyDataSeries plugin. Detailed help on importing and manipulating time series can be found there.

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