sscMap: an extensible Java application for connecting small-molecule drugs using gene-expression signatures.
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/sscMap.
Zhang
Shu-Dong
SD
MRC Toxicology Unit, Hodgkin Building, Lancaster Road, University of Leicester, Leicester, UK. sdz1@le.ac.uk
Gant
Timothy W
TW
D000818:Animals; D002460:Cell Line; D020650:Combinatorial Chemistry Techniques; D004967:Estrogens / Q000235:genetics; D015870:Gene Expression / Q000187:drug effects*; D006801:Humans; D051379:Mice; D051381:Rats; D054852:Small Molecule Libraries / Q000494:pharmacology*; D012985:Software Design
D004967:Estrogens; D054852:Small Molecule Libraries