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Google moves into genome data storage and analysis

18 November 2014

By Chris Baldacci

Appeared in BioNews 780

Google has announced that it will offer storage and analysis of genome sequencing data.

Every genome analysed in hospital and university labs takes up a lot of digital storage space - approximately 100 gigabytes per genome. Google has said it will store these large volumes of information in Google data centres and 'the cloud' from $25 a year - allowing scientists to easily access to their work and share knowledge among the research community.

This is not the first indication that Google hopes to move into the genetics market. In 2011 the company announced it was looking to help create and maintain a free genetic database in conjunction with a Californian startup, DNAnexus, after the US Government announced possible cuts to an online public genomic database, Sequence Read Archive (reported in BioNews 631).

David Glazer, the team leader for the new Google initiative, said: 'We saw biologists moving from studying one genome at a time to studying millions. The opportunity is how to apply breakthroughs in data technology to help with this transition.'

Advances in biological sciences and genetics have led to an explosion of data being captured by ever more sophisticated computers, but a great deal of this data is either not yet relevant or there are simply not enough people to read it - so storage is the only option. The US National Cancer Institute has reportedly taken up Google's offer and has already started moving its 2.6 petabyte database of cancer genomes to the Google cloud at a cost of $19 million.

Google will not only provide storage capability, but has also modified some of its search algorithms for genomic data analysis. Using an adapted version of BigQuery, a tool that started life as a spam filter, researchers will be able to compare thousands of genomes against each other simultaneously, all in the cloud.

SOURCES & REFERENCES
eWeek | 09 November 2014
 
Google Cloud Platform | 2014
 
The Scientist | 11 November 2014
 
MIT Technology Review | 06 November 2014
 

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