  Transcript enumeration methods such as SAGE, MPSS, and
sequencing-by-synthesis EST ``digital northern'', are important high-throughput
techniques for digital gene expression measurement. As other counting or voting
processes, these measurements constitute compositional data exhibiting
properties particular to the simplex space where the summation of the
components is constrained. These properties are not present on regular
Euclidean spaces, on which hybridization-based microarray data is often
modeled. Therefore, pattern recognition methods commonly used for microarray
data analysis may be non-informative for the data generated by transcript
enumeration techniques since they ignore certain fundamental properties of this
space. Here we present a software tool, Simcluster, designed to perform
clustering analysis for data on the simplex space. We present Simcluster as a
stand-alone command-line C package and as a user-friendly on-line tool. Both
versions are available at: http://xerad.systemsbiology.net/simcluster/ .
Simcluster is designed in accordance with a well-established mathematical
framework for compositional data analysis, which provides principled procedures
for dealing with the simplex space, and is thus applicable in a number of
contexts, including enumeration-based gene expression data.
