Powering NGS Workflows
As the costs of genomic sequencing continue to drop, there has been increasing demand for computing and data storage solutions. Many organizations are struggling to keep up. Regardless of whether you're working with genomic sequences in a research or clinical setting, Cray can help future-proof your lab with an upgradable compute infrastructure capable of managing your entire next-generation sequencing (NGS) ecosystem and scaling as your needs change.
De Novo Assembly at Scale
De novo assembly represents one of the most computationally challenging methods in biology, and it plays a critical role in metagenomics, agrigenomics and exploring certain regions of the human genome. Cray has helped researchers scale this difficult computation, delivering a complete de novo assembly of the human genome in under nine minutes.
Big Data Technologies to Contextualize NGS Results
For many researchers, a fully sequenced sample is where scientific exploration begins. The process of analyzing and interpreting next generation sequencing data can be significantly enhanced by using emerging big data technologies like Apache Spark™ and the Cray Graph Engine (CGE).
Apache Spark brings big data analytics to the masses, allowing researchers to quickly process, transform and explore mountains of NGS data — both structured and unstructured — in memory. Cray's Urika®-GX platform is engineered to deliver industry-leading performance executing Spark workflows.
The Cray Graph Engine allows researchers to take advantage of graph analytics at an unprecedented scale to support genomic interpretation and contextualization. CGE delivers this unique capability as an open standard SPARQL RDF database, making it easy to get started. By supporting open standards, CGE can immediately leverage important, publicly available data sources like EBI's Uniprot, Reactome and ChEMBL.
Accelerate your next-generation sequencing (NGS) with Cray.