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New TGen technology reduces storage needs and costs for genomic data

e 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.

Benefits shared with other institutes

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.

The software is available for download from

Technology springs from Next-Gen research

Dr. Tembe's motivation for G-SQZ came from the challenges involved in storing, processing, parsing and transferring enormous Next-Generation Sequencing data, which primarily is stored in plain text formats.

"Generating this data is one thing. It is quite another to store, query and manage it in an efficient manner, minimizing data-analysis bottlenecks and expediting the discovery process," Dr. Tembe said.

The G-SQZ approach is a novel application of Huffman coding of information, an idea first developed in the 1950s, which uses shorter codes for most

Contact: Steve Yozwiak
The Translational Genomics Research Institute

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