Case Study: University of Michigan accelerates genomics research with Google Cloud for Education

Google Cloud helps the University of Michigan’s TOPMed team process and share genomics data faster

The University of Michigan needed a faster, more scalable way to process and share massive genomics datasets for the TOPMed project, which had already generated petabytes of data and was growing toward 150,000 whole genome sequences. Working with Google for Education through Google Cloud Platform and Compute Engine, the university sought a cost-effective approach that could also support collaboration and reproducibility across a multi-institution research consortium.

Google for Education provided Google Cloud’s container-based infrastructure and Compute Engine Pre-emptible VMs to run genomic pipelines in smaller, efficient batches. The result was a dramatic acceleration in data preparation, compressing years of work into a few months and enabling researchers to begin analysis and discovery much sooner. Google for Education also helped broaden access to data through compatibility with NIH Data Commons and STRIDES, supporting secure sharing and collaboration for even smaller labs.

University of Michigan

Jonathon LeFaive

Senior App Programmer/Analyst, Department of Biostatistics