Case Study: Baylor College of Medicine achieves scalable, secure global genomic analysis and collaboration with Amazon Web Services

Baylor - Customer Case Study

Baylor College of Medicine’s Human Genome Sequencing Center (HGSC) supports the CHARGE consortium—a global effort to find genetic contributors to aging and heart disease—but faced massive data and infrastructure challenges. With hundreds of terabytes to petabytes of sequencing output, shipping encrypted hard drives to 200+ scientists was slow, insecure, and logistically impractical; provisioning local storage and compute was time-consuming, expensive, and could not keep pace with growing sequencer throughput or regulatory requirements.

Baylor partnered with DNAnexus and migrated its Mercury analysis pipeline to the DNAnexus PaaS on AWS, using Amazon S3/Glacier storage and EC2 compute with HIPAA-compliant security controls. The cloud-based workflow eliminated drive shipping, enabled cross‑platform tool sharing, and scaled to tens of thousands of cores; Baylor completed its first large analysis in 10 days (5× faster) using 21,000 cores, greatly accelerating collaboration and letting researchers focus on science instead of infrastructure.

Baylor College of Medicine

Narayanan Veeraraghavan

Lead Programmer Scientist