Partnership with India’s leading genome sequencing research institute leverages Lenovo high-performance Genomics Optimization and Scalability Tool (GOAST) architecture
Lenovo is collaborating with the CSIR Institute of Genomics and Integrative Biology (CSIR-IGIB) in a partnership to advance cancer research by digging deeper into the genetic roots of disease.
A vital part of the institute’s work revolves around human genetics research, which plays a critical role in identifying genetic disorders, characterizing the mutations that drive cancer progression, and tracking disease outbreaks. This partnership uses Lenovo’s Genomics Optimization and Scalability Tool (GOAST) architecture, featuring 2nd Gen Intel® Xeon® Scalable processors, to power through ultra-intensive genomic sequencing workloads and help researchers find insights faster. Lenovo’s GOAST is a high-performance computing (HPC) architecture engineered specifically for demanding genomics workloads that is a significant contributor to this initiative.
Working closely with Lenovo’s high-performance computing services, CSIR-IGIB deployed a 28-node system—the GOAST installation. By leveraging an optimised architecture and efficient open-source software, GOAST offers GPU-level performance at CPU-level costs, making it an attractive proposition for a public sector body such as CSIR-IGIB.
CSIR-IGIB has seen a significant performance impact from the Lenovo GOAST system for both whole genome sequencing (WGS) and whole exome sequencing (WES) workflows. On latency runs—where all resources of one node are assigned to executing a single job—the institute can complete a typical WGS and WES workflow 6.5 times faster.
Accelerated execution speeds enable researchers to process more samples and answer more complex questions in less time – from 60.5 hours to 9 hours. By sustaining a more rapid pace of research, CSIR-IGIB is able to push vital scientific work further, driving the breakthroughs needed to improve their understanding of diseases like cancer and find better treatments that improve patient outcomes and even save lives.
This Lenovo architecture will support an array of research initiatives, including ones focused on exploring the potential genetic roots of cancer. For example, researchers can compare cancer genomes against a standard reference genome to identify potential germline mutations (passed directly from a parent to a child) that can trigger or advance cancer development in humans. This would also enable improving our understanding of the genetic changes that can contribute to cancer; such analysis can also offer valuable insights into how an individual’s cancer might progress and its likely response to treatment.