Power Your Science
Google Genomics helps the life science community organize the world’s genomic information and make it accessible and useful. Big genomic data is here today, with petabytes rapidly growing toward exabytes. Through our extensions to Google Cloud Platform, you can apply the same technologies that power Google Search and Maps to securely store, process, explore, and share large, complex datasets.
Query the complete genomic information of large research projects in seconds. Process as many genomes and experiments as you like in parallel.
Whether you are working with one genome or one million, Google Genomics provides access to the power and flexibility you need to advance your work.
Google Genomics supports open industry standards, including those developed by the Global Alliance for Genomics and Health, so you can share your tools and data with your group, collaborators, or the broader community, if and when you choose.
Google’s infrastructure provides reliable information security that can meet or exceed the requirements of HIPAA and protected health information.
You create and collect lots of data that is valuable to researchers, developers and health organizations. With GCP you can better monetize the access and usage of your genomics data by hosting it in a storage bucket where operations, network and retrieval costs are easily billed to your clients.
GOOGLE GENOMICS FEATURES
Our implementation of the open standard from the Global Alliance for Genomics and Health is interoperable across multiple genome repositories and it’s backed by Google technologies like Bigtable and Spanner.
Google’s cloud infrastructure for your bioinformatics needs, including fast virtual machines, scalable storage, and a choice of fully managed SQL and NoSQL databases like Bigtable and Datastore.
Covered by our HIPAA Business Associates Agreement. Available via FedRAMP ATO for the National Cancer Institute Cancer Cloud Pilots.
Genomic data processing and analysis in real-time with BigQuery, in literate programming style with Cloud Datalab, in batch with GATK on Google Genomics, with Apache Spark or Cloud Dataflow, or with a Grid Engine cluster.
You can load up petabytes of sequence reads, variants, references, and annotations, and process them all efficiently.