Breaking Barriers in Platform Bioinformatics: The GPU-Accelerated Future With Intuitive Visual Interfaces That Ensure  Data Remains in Place

Parabricks Helps Tackle the Challenge of Computational Intractability in Bioinformatics 

Genomic research has made remarkable strides over the past decade. However, as the volume and complexity of genomic data continue to grow, researchers face significant hurdles in analyzing this data efficiently. A recent State of Science survey by the Linus Group revealed that the complexity of bioinformatics data analysis remains a top-of-mind barrier in life science research today, with one in four scientists citing it as their greatest challenge.

Challenge: Data Volume 

Next-generation sequencing technologies generate massive amounts of data, often terabytes for a single experiment. As genomic datasets grow larger, the demand for faster and more scalable analysis solutions becomes ever more crucial. Traditional CPU-based methods struggle to keep pace with this demand, leading to delays in research timelines and increased costs. Organizations need solutions that can scale effectively with their data needs while maintaining high performance. This is an ideal use case for Parabricks. Parabricks’ scalability with multiple GPUs provides a clear path for handling the ever-increasing complexity of genomic data analysis, ensuring that as datasets grow, computational capabilities can keep pace.

Challenge: Algorithmic Complexity

Algorithmic complexity presents significant challenges in computational biology and bioinformatics, particularly in omic data analysis. As datasets grow exponentially, many traditional algorithms become computationally infeasible, with execution times scaling prohibitively with input size. This often forces researchers to rely on heuristics or approximations, potentially compromising accuracy for speed. 

Parabricks helps address this challenge head-on by optimizing for the massive parallel processing capabilities of GPUs. By reimplementing industry-standard bioinformatics tools to take full advantage of the NVIDIA accelerated computing platform, Parabricks achieves up to 108x faster performance compared to CPU-based solutions, while providing equivalent results. This dramatic acceleration allows researchers to run complex algorithms on large genomic datasets in minutes rather than days, effectively pushing back the boundaries of what’s computationally feasible. 

These speed-ups not only save time but also enable researchers to tackle more complex problems and larger datasets, potentially leading to new insights and discoveries. 

Basepair’s Novel Hybrid SaaS Architecture and Intuitive Sample Based Pricing 

Although Basepair is pure SaaS (hence ultra-low operational burden), unlike most other bioinformatics platforms, it uniquely provisions in customers’ AWS accounts for both storage and compute. This enables organizations to be fully in control of their IT governance, security and most importantly from a cost perspective, their usage commitments with their cloud provider. Because this novel SaaS architecture delivers lower support and hosting costs for Basepair, Basepair can then pass on these savings to their customers. This manifests itself in its sample-based pricing structure, where on the one hand the pay-as-you-go per sample usage model is a very affordable way to get going if users have a small number of samples. On the opposite end of the spectrum, this same model scales to annual licenses for an unlimited sample volume at a set price, making it very cost-effective as analysis volumes grow. The latter in particular aligns well with the needs of large-scale genomic projects and allows for more transparent billing and predictable budgeting.

“Integrating NVIDIA Parabricks’ industry-leading performance with AWS ’ scalable cloud infrastructure and Basepair’s intuitive interface candramatically accelerate  and simplify omics data analysis,” said George Vacek, Global Head of Genomic Alliances at NVIDIA. “This collaboration lets scientists  spend less time on data processing and more time on groundbreaking discoveries that could improve human health.”

AWS HealthOmics and Basepair: A Powerful Combination for running Parabricks

The integration of AWS HealthOmics – including its Parabricks offerings – with Basepair’s user-friendly interface creates a synergy that addresses many of the enterprise challenges faced by organizations that work with omics data. In addition to cost savings, HealthOmics as a AWS service has been designed with scalability and robustness in mind, enabling organizations to reliably process tens of thousands of samples simultaneously without fear of things breaking. This is particularly needed to support the larger projects that are often seen in large pharma as well as for clinical organizations who cannot afford to have downtime in their production workloads where patient outcomes depend on reliability of turnaround time. 

Comprehensive Workflow Management

AWS HealthOmics provides a robust workflow engine and execution environment, allowing researchers to run bioinformatics workflows and analysis pipelines at scale. With Basepair’s intuitive GUI layered on top, users can now:

• Access, customize and execute “Ready to Run” workflows without needing command-line expertise.
• Explore and interact with the resulting processed data to accelerate time to scientific insight.
• Easily deploy custom workflows and tools to the broader R&D organization maintaining flexibility for specialized analyses.

Secure and Controlled Access

While AWS HealthOmics offers powerful capabilities, organizations often hesitate to provide widespread console access due to security and cost control concerns. Basepair addresses this by:

• Providing a controlled interface that limits user actions to necessary research tasks.
• Eliminating the need for individual scientists to access the AWS HealthOmics admin console directly.
• Maintaining organizational control over billing and resource allocation.

Optimized Storage and Compute

AWS HealthOmics is purpose-built for storing, querying, and analyzing genomic data. When combined with Basepair, organizations benefit from:

• Cost-effective storage solutions optimized for large-scale genomic data.
• Efficient data retrieval and querying capabilities that integrate seamlessly with analysis workflows.
• The ability to leverage AWS’s scalable compute resources without managing the underlying infrastructure.

Enhanced Collaboration and Reproducibility

The Basepair interface on AWS HealthOmics facilitates better collaboration and ensures reproducibility:

• Researchers can easily share workflows and results within their organization.
• Standardized environments reduce the “works on my machine” problem often encountered in bioinformatics.

Seamless Integration of NVIDIA Parabricks

With NVIDIA Parabricks available on AWS HealthOmics, and Basepair providing the user interface, researchers can:

• Leverage GPU-accelerated genomic analysis tools without needing expertise in GPU computing.
• Easily switch between CPU and GPU-based tools depending on the specific analysis requirements.
• Scale their GPU usage dynamically, optimizing for both performance and cost.
• Choose the plug-and-play option of the Basepair-hosted solution or provision in their own AWS account for compute and storage.

Cost Transparency and Control

The combination of AWS HealthOmics and Basepair offers improved cost management:

• Basepair’s sample-based pricing models provide both affordability and predictability for small- and large-scale projects alike.
• Organizations can leverage AWS’s cost optimization tools while maintaining ease of use for end users.
• The ability to easily optimize and switch between compute resources allows for fine-tuned cost control based on specific analysis needs.

By leveraging AWS HealthOmics through Basepair’s interface, organizations can harness the full power of cloud-based genomic analysis while maintaining ease of use, security, and cost-effectiveness. This combination addresses many of the key challenges in bioinformatics, from technical complexity to resource management, paving the way for FTE resources to spend time on what will ultimately differentiate them as opposed to commoditized necessities, accelerating genomic research and discovery.

A New Era in Omics Data Analysis

Basepair’s work with NVIDIA Parabricks and AWS HealthOmics signifies a new era within omics data analysis—one characterized not only increased accessibility but also improved efficiency and cost-effective  scalability. If you’re the leader of a team looking to streamline and enhance your organization’s ability to handle and analyze complex biological datasets, get in touch with your local Basepair representative or one of the point contacts below to book a demonstration.

Click here to try Parabricks on Basepair today.

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