Different types of high-throughput data are available in various databases for the cancer community. Integrating multi-omics and imaging data offers great potential in facilitating clinical decisions and discovery of therapeutic treatments for cancer patients. Cloud computing has emerged as a solution to address challenges of storing and analyzing these big data. However, rapid evolution of tools and technical complexity present major barriers to the adoption of cloud technologies in cancer research. This application aims to address these unmet computational challenges when using cloud computing to analyze multi-omics and imaging data. Towards this end, our working prototype with a graphical user interface called Biodepot-workflow-builder (Bwb) will be extended to support scientific imaging data analysis. Bwb provides an extensible platform to support interactive and performance optimized analysis of sequencing data on the cloud. In this application, accessible cloud-based analytical tools will be developed to support interactive and efficient analysis of multi-omics and imaging data from the Cancer Research Data Commons (CRDC). Most importantly, these analytical tools will target non-technical users by reducing the complexity of configuring and managing cloud resources. RandD effort will focus on accelerating compute intensive analytical tasks through the innovative use of cloud technologies
