Driving momentum in genomics research: AWS collaborates with Broad Institute

The cost of sequencing a human-sized genome has fallen to $1,000, from $10 million in 2007. As this figure continues to drop, data from genomic experiments is growing at a rate faster than computing capacities at most research institutes can handle.

The new price tag is driving researchers to make new strides in genomic research to identify, cure, and curtail diseases. While human beings are 99.9% identical in their genetic makeup, the remaining 0.1 percent tells a compelling story about why certain diseases occur. The ability to learn more – and faster – about an individual’s genomic information can reveal a lot.

Next-generation sequencing tools are now enabling genomic researchers and scientists to uncover these findings with greater speed, and deliver more timely clinical care. A new cloud collaboration is expanding on this potential.

Cromwell – a workflow management system from Broad, now on AWS

Cromwell is a workflow management system from Broad Institute of MIT and Harvard, a Cambridge, Massachusetts-based research institute that leverages the power of genomics to help us understand biology as well as treat human disease. Cromwell aims to facilitate scientific workflows for genome analysis. It enables genomic researchers, scientists, developers, and analysts to efficiently run their experiments, without deep expertise in computing capabilities. And it’s now on AWS.

The solution simplifies cloud computing tasks so that researchers can run their genomic workflows quickly and cost-effectively in the cloud. AWS Batch, a fully managed batch computing service, dynamically provisions the optimal quantity and type of compute resources – whether CPU or memory-optimized instances – based on volume and resource requirements for a set of batch jobs.

With Cromwell on AWS, researchers and scientists have even more flexibility to scale genomic experiments with the cloud.

Navigating peaks and troughs

Data generated from DNA sequencing and mapping in biomedicine, genomic medicine, and public health experiments can be spiky – with periodic peaks and troughs in processing times. This can mean idle capacity on computing resources available at a research facility.

The cloud offers the scientific community scalability, security, and reliability – and also the ability to pay only for the resources they need. Using “spot” computing instances in the cloud, rather than on-demand compute time, makes the cost of processing genomic experiments even more affordable. By taking advantage of Cromwell on AWS, researchers and scientists can make rapid progress in identifying genomes and feel more confident in their ability to experiment. Additionally, this is compute processing that keeps pace with the speed at which experimental data is generated.

Meeting researchers where they are

Genomic researchers and scientists are generally less interested in the mechanics of computing technology than in conducting genome analysis. Among its user friendly features, Cromwell helps make the computing process more transparent by using a straightforward syntax called Workflow Description Language – a human-readable and writable code. It similarly supports Common Workflow Language.

Next steps

To learn more about this solution for advancing genomic research, join us for a webinar. Discover tools, techniques, and best practices for developing and executing scientific workflows with Cromwell on AWS.