Scalable, Accelerated Genomic Sequence Analysis

Genomic research is pivotal for advancing bioenergy applications, a key interest of the Department of Energy (DOE). Massive genomic datasets are essential for developing sustainable biofuels and understanding environmental impacts. However, a critical bottleneck exists in "read mapping"—the process of aligning short DNA sequences to a reference genome—where the speed of DNA sequencing far exceeds the capacity of data analysis. This mismatch delays bioenergy research advancements and hampers the potential of genomics to drive innovations in sustainable energy solutions. Building on proven, published research - the first in-storage processing system designed for genomic sequence analysis - this Phase I project aims to develop a massively scalable, parallel implementation using standard commercial server infrastructure. By leveraging advanced parallel processing capabilities in our existing analytic data storage platform, we intend to significantly accelerate the read mapping process. This innovative approach will enhance the efficiency of genomic data analysis, directly benefiting bioenergy research by enabling faster discovery and development of sustainable biofuels. The project will focus on three key areas: (1) Enhance the storage of large genomic datasets within the innovative analytic data storage platform to improve efficiency and speed; (2) Accelerate Read Mapping by developing solutions to perform genetic sequence matching while data is stored within a distributed storage environment; and (3) Validate how this solution can be utilized for bioenergy research. This work will be supported by the researcher who developed the in-storage genomic sequencing technology as well as a university supporting the bioenergy validation. If successful, this project could revolutionize genomic data processing, reducing the time and cost of sequencing, with broad applications in healthcare, agriculture, and bioenergy. These improvements would advance scientific research, potentially leading to significant economic and environmental benefits.