SBIR Phase II: Whole Genome Sequencing - Data to Insight in One Hour

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to enhance precision medicine by reducing data processing time and cost, leading to faster results, higher genomic data processing throughput and, ultimately leading to better treatment of patients. Many diseases have their impacts locked in DNA data. Unlocking the data for an individual may provide a significant boost to human healthcare. By providing Whole Genome Sequencing (WGS) data analysis in one hour, as compared to the current standard of several days, and at a fraction of today's cost, DNA tests can become mainstream and research can be accelerated. WGS data is becoming a key component in ensuring correct and timely treatment of vulnerable populations, including newborn babies, people with cancer and rare diseases, and pregnant women. Correct prediction and treatment based on WGS data will extend human lives and promote better quality of life by accelerating the development and broad implementation of precision medicine. The intellectual merit of the proposed activity is to develop a cloud-based framework to accelerate whole genome sequencing data analysis. This SBIR Phase II project creates a software framework where multiple industry-standard genomic analyses will be accelerated transparently to run orders of magnitude faster, while reducing computational costs by up to 4x. The proposed innovation solves the scaling, performance, and cost challenges of WGS computing through novel parallelism extraction and mapping techniques. The framework under development for accelerating genomic analysis has been implemented to focus on GPUs and traditional processors (CPUs). Using this framework, secondary data analysis programs can use all the computing resources present in a standard computing node (CPU cores; GPUs), leading to higher utilization of the system and higher throughput. The GPU accelerates the data parallel portion of the software, while the CPU is mainly responsible for the orchestration of data between CPUs and GPUs, load balancing across multiple accelerators. By providing this framework to run on the cloud and on-premise, users can scale to meet the exploding demands of the DNA analysis industry. The software generates exact results to industry standard tools and does not sacrifice configurability that is critical for users. This framework also will enable researchers and medical professionals to analyze several thousands of genomes simultaneously, leading to higher quality results. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.