OOMPA PROJECT
Thresher
The Thresher
RForge 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 with
more advanced class discovery, clustering, and visualization.
Support
Support for all packages that are part of the OOMPA family uses a
common set of discussion forums and bug trackers:
List of Packages
 PCDimension
 The PCDiimension package, which was described in a paper by
M Wang and
colleagures, implements and automates a graphical Bayesian
method to determine the number of principal components that was introduced
by Auer
and Gervini in 2008. Wang's paper also introduces the idea of
"biological components", which shoud be thought of as an
intereptetable (if redundant) replacement for principal components.
 Thresher
 The Thresher package uses the PCDimension package as a starting
point to estimate the number of clusters present in a data set. The
key idea is that the number N of clusters should lie between N
and 2N+1 where N is the number of PC components. More
details can be found in another paper
by M Wang and
colleagues. The paper also points out that Thresher can remove
outliers at the same time as it determines clusters.
 Mercator
 The Mercator package was introduced in a paper
by Abrams
and colleagues. The package has multiple goals. First, it
impements a variety of binary distance metrics, Second, it provides
consistent interfaces to a variety of clustering and visualization
methods, with an emphasis on being able to color samples
consistently across different methods.
 RCytoGPS
 In Zach Abrams' PhD thesis, he developed an algorithm called
Cytogenetics Pattern Sleuth (CytoGPS) that can parse karyotypes
written in a standard text form known as
the International
System for Human Cytogenetic Nomenclature and convert them into
binary vectors accessible to modern machine learning methods. That
algorithm is available online
at http://cytogps.org/. The
RCytoGPS package (see the pair of papers by Abrams and colleagues
in BMC
Bioinfomratics
and Bioinformatics)
provides tools to import the output of the web site into R so it
can be analyzed and visualized.
 SillyPutty
 The SillyPutty package introduces a novel clustering
algorithm, based on optimizing silhouette widths. A manuscript
describing and evaluating the algorithm is in preparation; the
package will be submitted to CRAN when the manuscript is completed.
