At the Genomics Center
Next generation sequencing produces large amounts of data that require extensive computational processing to generate actionable information that can be contextualized by the end users - scientists, clinicians, policy makers, or the general public. The gap that exists between computational analysis and data delivery is the main obstacle for effective data utilization, data sharing, and turnaround between bioinformaticians and the end users. This gap has slowed the adoption of Next Generation Sequencing (NGS) in mainstream research and diagnostics. Building upon the data reporting and mining analytical platform that we developed at HSS to deliver and visualize RNA-seq data I extend its current capabilities to other next generation sequencing methods (CHIP-seq, ATAC-seq, and scRNA-seq). The goal of this project is to create and maintain a scalable, web-based data delivery platform for NGS data storage, management, and visualization.
Post-Bac Researcher, Hospital for Special Surgery