The Class Prediicton
project is one
component of the broader OOMPA Project produced by the
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
- 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