SAN DIEGO, April 27, 2015 /PRNewswire/ -- Edico Genome today announced that collaborative data generated with biochemists and geneticists from Harvard and Stanford Universities showed the DRAGEN™ Bio-IT Processor sped analysis of a whole genome sequence with 300x depth of coverage by tenfold, generating results in approximately six hours compared to 60 hours with standard software.
"Processing large amounts of sequencing data remains a challenge, especially for individual research and clinical labs, in terms of the computing resources and bioinformatics expertise required. The DRAGEN processor provides a promising solution for quickly analyzing the data," said Wenzhong Xiao, Ph.D., Director of the Immuno-Metabolic Computing Center at Massachusetts General Hospital, and leader of a Computational Genomics Lab at the Stanford Genome Technology Center.
Added Pieter van Rooyen, Ph.D., Chief Executive Officer of Edico Genome, "Deepening the coverage of a whole genome sequence from the standard 30x to 300x greatly increases the accuracy and reliability of results, which is increasingly important with the rise of precision medicine and the use of targeted therapies for cancer. However, until now analysis tools have not been able to process the associated tenfold increase in processing power and subsequent storage space required. This study shows that DRAGEN removes the otherwise prohibitive time and potentially cost barriers, enabling 300x depth of coverage to be feasibly achieved, which could ultimately lead to improved patient care."
In the study, the highly curated genome NA12878 with 300x depth of coverage was reanalyzed using DRAGEN. The speed and pipeline accuracy of the reanalysis was compared to a reference analysis with BWA/GATK software. Results using DRAGEN were obtained in six hours and 16 minutes, while results using BWA/GATK software were obtained in 60 hours and 28 minutes.
In addition, a receiver operating characteristic (ROC) curve showed the analysis with DRAGEN was comparable to the reference analysis with BWA/GATK software for both single nucleotide polymorphisms (SNP) and insertions or deletions (INDELs).
The benchmark genotype calls of NA12878 were developed by the Genome in a Bottle Consortium, an initiative led by the National Institute of Standards and Technology (NIST).
"We continue our collaboration with Edico to evaluate the DRAGEN pipeline of sequence analysis for a number of different applications in clinical genomics," said Dr. Xiao. "So far we see about tenfold reduction of processing time without a noticeable loss of sensitivity and specificity."
DRAGEN™ is a reconfigurable platform designed to massively accelerate secondary analysis of NGS, removing a key bottleneck in NGS workflow. DRAGEN is loaded with highly optimized algorithms for mapping, alignment, sorting and variant calling, and the flexible platform can be loaded with additional algorithms for a range of secondary analysis pipelines, such as whole genome or exome, RNAseq, methylome, microbiome and cancer. The solution can be integrated directly into NGS bioinformatics servers and sequencing instruments and is provided with accompanying software as a Platform-as-a-Service (PaaS). Interested parties may inquire about DRAGEN at http://www.edicogenome.com/dragen/get-dragen-now/.
About Edico Genome
Edico Genome, developer of the world's first next-generation sequencing Bio-IT processor, DRAGEN™, is helping usher in the new era of precision medicine by enabling customized treatments and data-driven insights tailored to the individual. At the heart of personalized medicine is next-generation sequencing (NGS), which is growing at an unprecedented pace. By increasing the speed and accuracy of NGS data analysis, such as whole genome sequencing, Edico Genome's computing platform makes it easier to discover links between DNA sequence variations and human disease, allowing clinicians and researchers to reveal answers more quickly. For more information, visit www.EdicoGenome.com and follow #DRAGENonFIRE.
Senior Director of Marketing
Monica May for Edico Genome
SOURCE Edico Genome