Golden Helix accelerates copy number variation detection methodology

Golden Helix, Inc., today announced the incorporation of technologies that will greatly accelerate genetic research. By enabling the company's SNP & Variation Suite software to run on off-the-shelf video graphics cards, or GPUs, operations that took hours or days can now be completed in a fraction of the time - and without the need for expensive compute clusters or resorting to cloud-based computing. This novel ability will dramatically accelerate many forms of computationally expensive genetic analyses, including that of next generation sequencing data.

“It's impressive to see benchmarks showing our CNV detection algorithm running 10 to 20 times faster on a GPU than on a similarly priced CPU”

Ongoing advances in genotyping and next-gen sequencing are making analysis more difficult and complex. Faced with the need to add computation capacity to address this, research teams have had to either buy expensive computers with more cores, build a cluster of networked computers and incur the overhead of managing a complex infrastructure, or resort to using external cloud-based computing. Meanwhile, the computational power of graphics cards has been progressively increasing due to the requirements of today's most advanced video games. GPUs can contain hundreds of microprocessors, but can be installed for a fraction of the price; even extremely fast GPUs cost less than $500.

Recognizing the advances possible with a GPU, other markets have begun to use this technology to their advantage, fields as diverse as oil exploration, graphic design, linear algebra, and even stock options pricing. Golden Helix is now putting this technology into the hands of genetic researchers to accelerate the examination of the ever-increasing amounts of genetic data.

"We've been witnessing the pendulum swinging toward centralization of genetic research as data is getting larger and larger and the analysis more complex," stated Christophe Lambert, president and CEO of Golden Helix. "Unfortunately, only a small number of elite institutions have the resources for massive clusters and petabytes of disk storage. Those with fewer on-site resources are at a disadvantage in terms of pursuing high impact research. To the extent that we can keep bioinformatics on the desktop or small server, we can continue to make this kind of research feasible for the broader community of researchers who are fiscally constrained. Exploiting the power of GPUs is one way to achieve this end."

In its first application of this technology, Golden Helix has accelerated its copy number variation (CNV) detection methodology. Achieving optimal CNV detection requires enormous computational power that can take weeks on even the fastest desktop computers.

According to Gabe Rudy, vice president of product development at Golden Helix, the copy number problem is an ideal candidate for utilizing the potential of the GPU. "It's impressive to see benchmarks showing our CNV detection algorithm running 10 to 20 times faster on a GPU than on a similarly priced CPU" he said. "You see huge improvements even with a comparatively low-end GPU. In the end, researchers can spend more time working with their data and less time watching the progress bar creep across the screen."

Dr. Lambert concluded, "The only downside we see of using a GPU is the temptation for grad students to play video games while their professors aren't looking!"

The SNP & Variation Suite (SVS) is Golden Helix' integrated collection of high-performance analytic tools for rich, multi-dimensional approaches to uncovering genetic causes of disease and other conditions. The next version of SVS (v7.4) includes the new GPU capabilities and will be released in November.