Garvan Institute Integrates Geneformics Technology to Reduce Genomics Data Footprint
Geneformics Data Systems Limited, a leader in Genomics IT Infrastructures that advance the accessibility of transfer, storage and archiving of Next Generation Sequencing (NGS) today announced that the Garvan Institute of Medical Research will integrate Geneformics technology into its workflows. The Garvan Institute was one of the first centers in the world to acquire advanced next generation sequencing technology that is capable of sequencing up to 18,000 genomes a year.
Storage and archive of genomic data is becoming a huge challenge for the industry with a single whole human genome (WGS) generating approximately 300GB of raw, uncompressed data. Other compression technologies can reduce file size between 25 and 33 percent, while Geneformics true lossless technology compression reduces whole genome data size by up to 95 percent. Integrating Geneformics workflows means genomic data occupies a smaller footprint, which reduces storage costs, enables easier data sharing and increases flexibility to compute in other environments like the cloud.
“The combination of Geneformics’ technology and Garvan’s workflow will enable Garvan to benefit from storage and archiving of key bioIT and medical discoveries,” said Rafael Feitelberg, Geneformics CEO. “With our true lossless compression, we mitigate hurdles, making the data accessible so organizations can focus on genomic data insights including precision medicine research.”
“We looked for a solution to reduce our genomic data footprint and after extensive evaluation and testing, Geneformics was the clear choice,” said Warren Kaplan, Chief of Informatics at the Garvan Institute. “Geneformics offers superior compression ratio, the full integrity and lossless aspect of their solution and higher compression and decompression speed. By providing one of the most powerful technology platforms for using sequence data at scale and in real-time, we have the capabilities and know-how required to generate and deploy the necessary data to identify key variants in the genome that underlie an individual’s phenotype.”