TGen develops G-SQZ technique for genomic data processing

G-SQZ provides scientists with compact format for genomic data processing

A new computer data compression technique called Genomic SQueeZ (G-SQZ), developed by the Translational Genomics Research Institute (TGen), will allow genetic researchers and others to store, analyze and share massive volumes of data in less space and at lower cost.

Created specifically for genomic sequencing data, the encoding method underlying G-SQZ and its software use are described in a paper published today in the journal Bioinformatics.

Tests show that G-SQZ can compress data by as much as 80 percent while maintaining the relative order of the data and allowing for selective content access. This could save researchers and others millions of dollars worldwide.

Plans are to make the G-SQZ program freely available for research and academic use, and to explore commercial opportunities in genomic data storage and processing. TGen has filed a patent application for the G-SQZ technology.

"Data storage and processing costs are becoming a large factor in research planning as high-throughput genomic sequencing studies continue to generate increasing amounts of data. G-SQZ has the potential to save individual institutes hundreds of thousands of dollars per year in storage costs," said Dr. Waibhav Tembe, the paper's lead author and TGen's Senior Computational Scientist, who led the development of the G-SQZ algorithm and its software.

Enormous computing power is required to conduct today's cutting-edge analysis of large volumes of genomic sequencing data. This data is critical in studying the genes that are a part of the 3-billion-letter DNA sequence, the entire genome of one person. Such analysis is enabling researchers to identify those genomic components that either prevent or contribute to diseases, such as cancer, diabetes and Alzheimer's, and to discover treatments tailored to individual patients that can prolong and increase their quality of life.

Today's genomic sequence analysis requires analyzing terabytes of data. Large sequencing centers are planning or have installed petabyte-scale storage. One terabyte is more than 1 trillion bytes of data. One petabyte is 1,000 terabytes.

Dr. Edward Suh, TGen's Chief Information Officer, described G-SQZ as a significant breakthrough in storing and analyzing ever-increasing genomic sequencing data.

"As a non-profit research institute dedicated to advancing science for the public good, we at TGen are proud to be able to share aspects of this technology with other non-profit research institutes, especially in these times of tightened budgets," said Dr. Suh, who also is a Senior Investigator at TGen and co-author of the paper.

James Lowey, TGen's Director of High-Performance Biocomputing and the third co-author of the paper, said reducing storage costs for genomic technology has the potential to eventually lead to a chain reaction of lower health costs for medical institutions and, ultimately, for patients.

"When you reduce the need for storage, you also are reducing your overhead costs, such as electricity and space, and that can save money," Lowey said.