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Class Prediction

The Class Prediicton R-Forge project is one component of the broader OOMPA Project produced by the Coombes Lab over the past decade. it consists of a set of packages to help select features and build models in order to predict binary outcomes from omics data sets.


Support for all packages that are part of the OOMPA family uses a common set of discussion forums and bug trackers:

List of Packages

The Bimodality Index is a tool developed in a paper by Wang and colleagues to identify features with bimodal distributions. The motivating idea is that bimodally expressed featuires are always markers of something; hopefully, a collection of those somethings will be related to the outcome to be predicted. See also this paper by Tong and colleagues and the SIBER package for an extension of this idea to RNA-Sequencing data.
The Modeler package provides classes and methods for training and using binary prediction models. it implements a variety of methods for filtering features (i.e., removing features that you are sure won't help), feature selection, and model construction. These are all provided with a common interface that allows you to use them in other contexts such as cross validation.
The CrossValidate package provides classes and methods for cross validation of class prediction models. These work with Modeler objects, but can make sure that feature filtering or feature selection are included properly within the cross-validation loop.
This package implements a genetic algorithm in a form that can be used for feature selection.
The ClassPrediction package provides no new functionality. The only thing it does is automatically load the GenAlgo and CrosValidate packages for concurrent usage.

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