High-throughput clinical NGS data analysis on the cloud

3^rd International Conference on Genomics & Pharmacogenomics

September 21-23, 2015 San Antonio, USA

Yassine Souilmi1,2, Alex K Lancaster1, Jae-Yoon Jung1, Ettore Rizzo3, Ryan Powles1, Peter J Tonellato1 and Dennis P Wall4

1Harvard Medical School, USA 2Mohamed V University-Agdal, Morocco 3University of Pavia, Italy 4Stanford University, USA

Posters-Accepted Abstracts: J Mol Genet Med

Abstract :

The dramatic fall of Next Generation Sequencing (NGS) cost in recent years positions the price in range of typical medical testing, and thus Whole Genome Analysis (WGA) may be a viable clinical diagnostic tool. Modern sequencing platforms routinely generate petabyte data. The current challenge lies in calling and analyzing this large-scale data, which has become the new time and cost rate-limiting step. To address the computational limitations and optimize the cost, we have developed COSMOS, a scalable, parallelizable workflow management system running on cloud services. Using COSMOS, we have constructed a NGS analysis pipeline implementing the Genome Analysis Toolkit - GATK v3.1 - best practice protocol, a widely accepted industry standard developed by the Broad Institute. COSMOS performs a thorough sequence analysis, including quality control, alignment, variant calling and an unprecedented level of annotation using a custom extension of ANNOVAR. COSMOS takes advantage of parallelization and the resources of a high-performance compute cluster, either local or in the cloud, to process datasets of up to the petabyte scale, which is becoming standard in NGS. This approach enables the timely and cost-effective implementation of NGS analysis, allowing for it to be used in a clinical setting and translational medicine. With COSMOS we reduced the whole genome data analysis cost under the $100 barrier, placing it within a reimbursable cost point and in clinical time, providing a significant change to the landscape of genomic analysis and cement the utility of cloud environment as a resource for Petabyte-scale genomic research.

Biography :

Email: Yassine_Souilmi@hms.harvard.edu