QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Gene expression connectivity mapping is a valuable research tool, particularly for identifying small molecule compounds for disease treatment and drug repurposing.
• The Library of Integrated Cellular Signatures (LINCS) program has significantly expanded the available data for gene expression connectivity mapping in biomedicine.

Purpose of the Study:

• To introduce QUADrATiC, a user-friendly software tool for exploring gene expression connectivity within the LINCS dataset.
• To enable the identification of FDA-approved small molecule compounds for therapeutic repurposing.

Main Methods:

• QUADrATiC leverages multicore computing architectures and the Akka framework for scalable data processing, accommodating large datasets.
• A Graphical User Interface (GUI) developed with Javascript frameworks offers advanced visualization capabilities.
• A web services interface facilitates integration with other programs and scripts.

Main Results:

• QUADrATiC provides a user-friendly platform for analyzing gene expression connectivity on LINCS data, focusing on FDA-approved compounds.
• The software demonstrates scalability and improved performance compared to existing tools.
• Novel visualization features enhance the analysis of gene expression connections.

Conclusions:

• QUADrATiC improves upon existing connectivity map software in scope, applicability, usability, and speed.
• The tool empowers biological researchers to analyze transcriptional data and identify potential therapeutics.
• QUADrATiC offers a significant advancement in investigating gene expression connectivity, yielding more biologically relevant results.