Nilesh Kavthekar

Bio: Nilesh Kavthekar is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Data management & Workflow. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Distributed tools deployment and management for multiple galaxy instances in globus genomics

Abstract: Workflow systems play an important role in the analysis of the fast-growing genomics data produced by low-cost next generation sequencing (NGS) technologies. Many biomedical research groups lack the expertise to assemble and run the sophisticated computational pipelines required for high-throughput analysis of such data. There is an urgent need for services that can allow researchers to run their analytical workflows where they can define their own research methodologies by selecting the tools of their interest. We present the challenges associated with managing multiple Galaxy instances on the cloud for various research groups using Globus Genomics, a cloud based platform-as-a-service (PaaS) that provides the Galaxy workflow system as a hosted service along with data management capabilities using Globus Online. We address the unique challenges, our strategy, and a tool for automatically deploying and managing hundreds of analytical tools coming from the public Galaxy Tool Shed, new tools wrapped by our group, and tools wrapped by end users across multiple Galaxy instances hosted with Globus Genomics.

A case study for cloud based high throughput analysis of NGS data using the globus genomics system

Abstract: Next generation sequencing (NGS) technologies produce massive amounts of data requiring a powerful computational infrastructure, high quality bioinformatics software, and skilled personnel to operate the tools. We present a case study of a practical solution to this data management and analysis challenge that simplifies terabyte scale data handling and provides advanced tools for NGS data analysis. These capabilities are implemented using the “Globus Genomics” system, which is an enhanced Galaxy workflow system made available as a service that offers users the capability to process and transfer data easily, reliably and quickly to address end-to-endNGS analysis requirements. The Globus Genomics system is built on Amazon 's cloud computing infrastructure. The system takes advantage of elastic scaling of compute resources to run multiple workflows in parallel and it also helps meet the scale-out analysis needs of modern translational genomics research.