Webinar on scalable compute architecture

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QIAGEN Digital Insights

Webinar on scalable compute architecture

How much compute power do you need to analyze 10 gene panels, exomes, or genomes each day? What about 1,000 genomes each week?

Questions about compute infrastructure are among the most common we hear from our customers, and this has been the primary motivator for our collaboration with Intel. Together, we’ve been working to support affordable, massively scalable whole-genome analysis based on Intel’s world-class infrastructure and our industry-leading analysis tools.

Earlier this year we released the reference architecture that came from this collaboration, and you can learn more about it in the webinar below featuring Michael McManus, Senior Health & Life Sciences Solution Architect at Intel, and Mikael Flensborg, Director and Solution Lead for QIAGEN Bioinformatics. The speakers will update you on the new architecture, which combines our Biomedical Genomics Solution with the Intel Scalable System Framework. They’ll also share advice on sizing and building a genomics cluster based on data-generation needs, as well as how to scale the cluster as demand changes.

The solution represents some of the code optimization work that Intel has focused on lately, teaming up with industry leaders such as QIAGEN Bioinformatics to improve algorithms based on the latest multi-core chip architecture. As genome analysis tools become increasingly complex — newer haplotype-aware callers, for instance, are far more computationally intense than older generations of variant callers — there is greater need for scientists to become experts in computational infrastructure. With solutions like the QIAGEN/Intel reference architecture, we alleviate that burden by recommending a scalable, easily managed system that allows users to focus instead on the science.

For example, this system meets the computational and analysis demands of Illumina’s HiSeq X Ten while providing whole-genome analysis for as little as $22 per genome. With Intel’s 32-node cluster, researchers can save as much as $1.3 million in total ownership costs compared to a vendor-recommended BWA+GATK variant calling pipeline run on an 85-node cluster.

Learn more about our High volume sequencing solution

Webinar

Reference Architectures for the QIAGEN Biomedical Genomics Solution