sscMap: An extensible Java application for connecting small-molecule drugs using gene-expression signatures

TL;DR

sscMap is a Java tool that enables researchers to identify connections between gene expression signatures and small-molecule drugs, facilitating drug discovery and toxicology studies by leveraging extensive public datasets and customizable profiles.

Contribution

The paper introduces sscMap, a Java application that implements a new connectivity mapping method with customizable reference profiles and broad applicability to various 'omics technologies.

Findings

Includes a default reference dataset with over 7000 microarrays.

Allows addition of custom reference profiles for personalized analysis.

Facilitates statistically significant connections between gene signatures and drugs.

Abstract

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