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Amazon has unveiled exciting new features aimed at enhancing the integration of omics data storage and analytical tools. The advancements come as part of a broader initiative to deepen personalized healthcare through multi-omics data, which is crucial for applications ranging from population sequencing to drug discovery and diagnostics research. While the potential of omics data is well-recognized, our healthcare and life sciences (HCLS) clients have been seeking more effective tools to initiate projects, develop applications, and scale analyses. These enhancements are designed to reduce costs and expedite insights.
Since launching AWS HealthOmics at re:Invent 2022, we have empowered HCLS organizations to efficiently store, query, and analyze genomic, transcriptomic, proteomic, and other omics data. Many customers and partners have adopted HealthOmics to manage their omics data and execute bioinformatics analysis pipelines at scale, which has allowed them to dedicate more time to their research rather than infrastructure management.
In various scenarios, clients express the need for omics-focused storage that seamlessly integrates with their existing systems. The significant costs associated with large-scale storage of genomic and other omics data can lead to difficult decisions about whether to discard data, limit analyses, or resort to compression formats that can hinder accessibility. All these choices necessitate personnel with expertise in biology and computation to determine the best strategies, often resulting in research delays and budget overruns.
To facilitate these decisions, we are pleased to announce that objects stored in the HealthOmics sequence store now feature Amazon S3 URIs, enabling them to be accessed via S3 API-compatible tools. The sequence store already provides benefits through its domain-specific metadata, cost savings from compression and tiering, and scalability. With this new capability, customers only need to configure IAM permissions to integrate sequence stores with their current analysis tools. This means users can adopt HealthOmics data stores without disrupting their scientific work. We’re already seeing this new functionality in action among customers like Genomics England, and partners such as BioTools, Quilt, Clovertex, and Memverge.
The HealthOmics sequence stores allow clients to store FASTQ, uBAM, BAM, and CRAM files in a cost-effective manner at scale. These stores organize data by grouping files and domain-specific metadata into a “read set” object. Automated tiering and compression help optimize costs while ensuring quick access to the data. Previously, customers could only access active read sets through HealthOmics APIs or via bulk export to Amazon S3, which required adjustments to their analysis or data sharing workflows and slowed down the integration process.
With the new S3 URI capability, customers can directly list and read active read sets using S3 APIs. This feature, which utilizes S3 access points to create S3 URIs, organizes sequence stores hierarchically, making it easy for customers to navigate files using S3 List APIs and retrieve them using S3 Get APIs. Furthermore, this structure, along with resource tags for subject and sample IDs, enables customers to establish IAM access policies tailored to their needs.
Many bioinformatics tools already support Amazon S3 APIs, including analysis tools like the Integrated Genome Viewer (IGV), workflow engines such as CWL, WDL, Nextflow, Snakemake, and libraries like Samtools and HTSlib. Thanks to the S3 URI feature, these tools can now be utilized with the objects in HealthOmics data stores, requiring only the appropriate IAM permissions for configuration.
“Genomics England is at the forefront of genomic medicine and research, supporting the NHS’s pioneering whole genome sequencing service and managing the expanding National Genomic Research Library. We’re leveraging AWS HealthOmics to achieve cost savings in cloud storage as we scale our sequencing initiatives. We’re excited about the sequence store S3 URI feature, which will enhance our users’ experience in analysis without the need for changes,” stated Laura Matthews, Chief Technology Officer, Genomics England.
“Basepair is committed to making bioinformatics more accessible and efficient through our point-and-click platform. Collaborating with AWS, we recently announced the integration of AWS HealthOmics with our platform, enhancing our workflow and storage capabilities. The S3 URI feature allowed for quick integration with our visualization tools in less than a day,” remarked John Davis, Founder & CEO, Basepair.
“Clovertex specializes in IT services for scientific applications on AWS. We are enthusiastic about the new AWS HealthOmics S3 URI feature, which simplifies data analysis by bypassing unnecessary data transfer steps. This has enabled us to swiftly integrate HealthOmics storage with various workflows and analytical tools, allowing scientists to concentrate on deriving insights from their data,” said Sarah Jenkins, VP of Scientific Strategy, Clovertex.
“Quilt focuses on connecting disparate data silos through immutable data packages. The introduction of the HealthOmics S3 URI features excites us, as it allows our customers to merge sequence stores with traditional S3 objects into cohesive, trustworthy data products for their Amazon data lakes. We look forward to extending our Quilt Catalog to facilitate easy interaction with HealthOmics data,” noted Michael Brown, Director of Product, Quilt Data, Inc.
In conclusion, the introduction of data store S3 URIs equips healthcare and life sciences organizations with new capabilities to enhance the scalability of their research and expedite scientific discovery. For more insights into workplace dynamics, check out this blog post about communication styles and their impact on work environments, which can be found at Career Contessa. For information regarding federal contracts and wage increases, visit SHRM. Additionally, the Amazon Fulfillment Center Safety and Training resource is an excellent guide for best practices in the workplace.
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