Background: Connectivity mapping is a process to recognize novel
pharmacological and toxicological properties in small molecules by comparing
their gene expression signatures with others in a database. A simple and robust
method for connectivity mapping with increased specificity and sensitivity was
recently developed, and its utility demonstrated using experimentally derived
gene signatures.
Results: This paper introduces sscMap (statistically significant connections'
map), a Java application designed to undertake connectivity mapping tasks using
the recently published method. The software is bundled with a default
collection of reference gene-expression profiles based on the publicly
available dataset from the Broad Institute Connectivity Map 02, which includes
data from over 7000 Affymetrix microarrays, for over 1000 small-molecule
compounds, and 6100 treatment instances in 5 human cell lines. In addition, the
application allows users to add their custom collections of reference profiles
and is applicable to a wide range of other 'omics technologies.
Conclusions: The utility of sscMap is two fold. First, it serves to make
statistically significant connections between a user-supplied gene signature
and the 6100 core reference profiles based on the Broad Institute expanded
dataset. Second, it allows users to apply the same improved method to
custom-built reference profiles which can be added to the database for future
referencing. The software can be freely downloaded from
http://purl.oclc.org/NET/sscMapComment: 3 pages, 1 table, 1 eps figur