Case Study: Virginia Polytechnic Institute and State University achieves scalable, cost‑saving genomic analysis with Microsoft Azure

University Transforms Life Sciences Research with Big Data Solution in the Cloud

Virginia Tech, a leading U.S. research university, faced a growing bottleneck as next‑generation sequencers began producing petabytes of genomic data—far outstripping the storage and supercomputing resources available to many life‑science researchers. The university needed a scalable, cost‑effective way to give scientists access to high‑performance analysis tools without building and maintaining expensive local data centers.

The school’s computer‑science team, supported by an NSF/Microsoft program, built an on‑demand cloud model on Windows Azure HDInsight, creating SeqInCloud (a GATK‑based pipeline) and CloudFlow (a client/cloud workflow manager) to optimize data partitioning, transfers, and on‑demand cluster provisioning. The solution reduced costs by avoiding permanent infrastructure investments, enabled collaborative, anywhere access to sequencing workflows, sped up and improved analyses, and has drawn interest from other top research institutions.

Virginia Polytechnic Institute and State University

Wu Feng

Professor of Computer Science