The team analyzed a pediatric cohort of 1,000 whole genomes from the Center for Applied Genomics (CAG), a specialized Center of Emphasis at CHOP with the primary goal of translating basic research findings to medical innovations. These samples were carefully curated to reflect the composition of the entire biobank and represent the most common complex disorders and rare single-gene diseases. Each patient’s data had previously been de-identified to protect personal privacy. Making use of the AWS Cloud allowed the team to simultaneously draw on the combined computing power of 1,000 field programmable gate array (FPGA) enabled Amazon EC2 F1 instances.
More than 60 percent of the samples were from African Americans, making it one of the largest cohorts for this demographic that has been sequenced to date. Results from the rapid analysis will be utilized by the CAG with the hope of uncovering genetic links to common childhood diseases, including asthma, autism, diabetes, epilepsy, obesity, schizophrenia, pediatric cancer and a range of rare diseases. The CAG is dedicated to the development of new and better ways to diagnose and treat children affected by rare and complex medical disorders.
“When it comes to delivering critical diagnoses to our patients, speed — combined with accuracy — are of the utmost importance,” said Hakon Hakonarson, M.D., Ph.D., director of CAG at CHOP. “Today’s speed test is a culmination of two years of collaboration between CAG and Edico Genome, including beta-testing their product in our center. We utilize DRAGEN as part of our genomic workflow to achieve our mission of translating basic research findings to medical innovations. The speed of this technology in processing vast amounts of raw data in a matter of minutes will allow us to deliver actionable results in hours—an important capability as we go forward in realizing the benefits of precision medicine for children and families.”
Today’s technological tour de force, performed at the American Society of Human Genetics 2017 Annual Meeting, (ASHG 2017) set the GUINNESS WORLD RECORDS title for Fastest time to analyze 1,000 human genomes. The title was presented onsite by an official GUINNESS WORLD RECORDS adjudicator.
Analysis began with the streaming of the 1,000 data files in standard FASTQ format from Amazon Simple Storage Service (Amazon S3) to 1,000 Amazon EC2 F1.2xlarge instances upon which the DRAGEN Genome Pipeline was deployed. The pipeline consisted of mapping, aligning, sorting, duplicate marking and haplotype variant calling and ended when a variant call format (VCF) file was delivered back to a secure Amazon S3 bucket. The Amazon EC2 F1 instances, supported by AWS, utilize Xilinx Virtex UltraScale+ field programmable gate arrays (FPGAs) to deliver performance at scale on the cloud. AWS is a leading, secure cloud services platform, offering compute power, database storage, and other functionality to help businesses scale and grow.
“CHOP is a pioneer in integrating next-generation sequencing into clinical care, utilizing cutting-edge technologies to provide its patients with the most rapid and accurate information,” said Pieter van Rooyen, Ph.D., chief executive officer at Edico Genome. “With solutions that expedite their analysis turnaround times, centers such as CHOP are able to discover potentially life-saving results in a fraction of the time, while maintaining high accuracy.”
DRAGEN rapidly accelerates next-generation sequencing (NGS) data analysis, providing high accuracy while reducing costs. DRAGEN’s ultra-rapid analysis can be achieved onsite via a 1U Dell 4130 server or on the AWS cloud through a number of partners, including AWS Marketplace, BaseSpace Sequence Hub and DNAnexus. By design, DRAGEN’s speed does not compromise accuracy, and the platform received high scores across all accuracy metrics in the recent PrecisionFDA Hidden Treasures – Warm Up Challenge.
The GUINNESS WORLD RECORDS title will be granted upon publication of the results in a peer-reviewed journal.
Visit Edico Genome at booth #710 at ASHG. For more information about DRAGEN, visit www.edicogenome.com/DRAGEN.