OOMPA
OOMPA Core Packages
- oompaBase
- Class Unions, Matrix Operations, and Color Schemes for
OOMPA. Provides class unions that must be preloaded in order
for the basic tools in the OOMPA project to be defined and loaded. It also
includes vectorized operations for row-by-row means, variances, and
t-tests. Finally, it provides new color schemes.
- oompaData
- Data to Illustrate OOMPA Algorithms. This is a data-only
package to provide example data for other packages that are part of
the OOMPA suite of packages.
- PreProcess
- Basic Functions for Pre-Processing Microarrays. Provides
classes to pre-process microarray gene expression data as part of
the OOMPA collection of packages.
- ClassComparison
- Classes and Methods for "Class Comparison" Problems on
Microarrays. Defines the classes used for "class comparison"
problems in the OOMPA project. Class comparison includes tests for
differential expression; see Simon's book for details on typical
problem types.
- ClassDiscovery
- Classes and Methods for "Class Discovery" with Microarrays or
Proteomics. Defines the classes used for "class discovery"
problems in the OOMPA project. Class discovery primarily consists of
unsupervised clustering methods with attempts to assess their
statistical significance.
- TailRank
- The Tail-Rank Statistic. Implements the tail-rank
statistic for selecting biomarkers from a microarray data set, an
efficient nonparametric test focused on the distributional
tails. See the
Tolstoy paper.
- Polychrome
- Qualitative Palettes with Many Colors. Tools for
creating, viewing, and assessing qualitative palettes with many
(20-30 or more)
colors. See Coombes
and colleagues (2019).
- plasma
- Partial LeAst Squares for Multiomic Analysis. Contains
tools for supervised analyes of incomplete, overlapping multi-omics
datasets.
See Yamaguchi
and colleagues (2025).
- Preservation
- Assessing Preservation for Dimension Reduction
Algorithms. Contains tools to compute metrics that can compare
the performance of dimension reduction algorithms for the
preservation of pairwise distances, neighborhoods, or paths. For
distances and neighborhoods, see
. Under Development.
- NumClust
- Finding the Number of Clusters. Implements methods to
estimate the "true" number of clusters in a data set. Under
Development.
- BetaModels
- Bayesian Analysis of Different Rates in Different
Groups. Test for different proportions (rates) in different
groups using a Bayesian model in which all rate parameters follow a
beta distribution and are selected from a common
hyperdistribution. Includes tools to fit an arbitrary mixture of
beta distributions. Under Development.
- BlockMaker
- Statistical Interpretation of Heatmaps. Provides tools to
test the statistical significance of structures within two-way
clustered heatmaps. More details can be found at
.
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