Precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person,” according to the Precision Medicine Initiative. This approach allows doctors and researchers to identify and tailor treatments for groups of patients to improve patient outcomes. Precision medicine is powered by studying genomics data from hundreds of thousands of people refining the understanding of normal and disease diversity. The challenge is to turn the genomics data from many large-scale efforts like biobanks, research studies, and biopharma, into useful insights and patient-centric treatments in a rapid, reproducible, and cost-effective manner. The key to enabling scientific discovery is to combine different data streams, ensure global accessibility and availability, and allow high-performance data processing while keeping this sensitive data secure. “The responsible and secure sharing of genomic and health data is key to accelerating research and improving human health,” is a stated objective for the Global Alliance for Genomics and Health (GA4GH). This approach requires technical knowledge and ever-growing compute and storage resources. One of the ways that AWS is enabling this objective is to host many genomics datasets in the Registry of Open Data on AWS.
Raw genomics data is typically processed through a series of steps as part of a pipeline to transform into a form that is ready for analysis. Each step of the secondary analysis workflow could have different compute and memory requirements; some of the steps could be as simple as adding a set of annotations, or as computationally intensive as aligning raw reads to a reference genome. The requirements at this stage are to process the data in a cost effective, scalable, efficient, consistent, and reproducible manner across large datasets.
