How is Genomic Data Stored?
Advances in sequencing technologies have allowed us to analyze DNA sequences with incredible precision, but the size and speed of production of these datasets is rapidly increasing. If a person were to type the human genome letter for letter, it would form a stack of paper as tall as the Empire State Building.
Datasets of this scale need high-throughput processing and analysis tools to be analyzed fast enough to be applied to complex biomedical problems and help improve people’s lives. However, many researchers are swimming in data, which can slow their research down. This is where cloud storage comes into play.
Advantages of Cloud Storage
The volume of sequence data that gets stored rather than immediately analyzed can be up to terabytes in only the span of a day. Traditionally, data was stored “on-premise” (also called on-prem), meaning that a given lab or company had to buy physical servers and infrastructure to store their data.
On-prem data storage solutions struggle to keep up with these vast data outputs and can quickly run out of space, leading to investing huge sums of money in the constant expansion of on-prem storage. Cloud-based storage provides greater availability, scalability, and durability and is an excellent solution for storing genomic datasets.
What Does Cloud Storage Look Like In Practice?
There are many cloud storage platforms to choose from: one example is the popular cloud storage platform AWS S3. It allows researchers to make their data accessible to the research communities of their choice and/or move the data to archival storage, all while minimizing costs and meeting regulatory requirements for confidential data storage.
This is made possible by different storage classes to provide a custom fit to a researcher’s needs. Classes and costs are determined by the quantity of data and the frequency and speed of access. Archived or infrequently accessed data is less expensive to store while data that needs to be rapidly and frequently available for analysis falls in a more expensive storage class.
Outsourcing Cloud Management: How We Can Help
Storing your sequence data in a secure, dynamic cloud environment is essential for success in modern genomics research. We can design custom cloud infrastructure that fits your data needs. Bridge Informatics’ experts are trained in various cloud environments, so they understand the common questions and challenges associated with cloud computing and data storage. Click here to schedule a free introductory call with a member of our team.
Dan Ryder, MPH, PhD
Dan is the founder and CEO of Bridge Informatics, a professional services firm helping pharmaceutical companies translate genomic data into medicine. Unlike any other data analytics firm, Bridge forges sustainable communication change between their client’s biological and computational scientists. Dan is passionate about improving communication between people of different scientific backgrounds, enabling bioinformaticians and software engineers to succeed collectively.
Prior to forming Bridge Informatics, Dan served in a variety of roles helping pharmaceutical clients solve early-phase drug discovery and development challenges. Dan received both a Ph.D. in Biochemistry and Molecular Biology and an MPH in Disease Control from the University of Texas Health Science Center at Houston (UTHealth Houston). He completed his postdoctoral studies in Molecular Pathways of Energy Metabolism at the University of Florida College of Medicine. Dan received his undergraduate degree in Microbiology from the University of Texas at Austin. Click here to connect with Dan on LinkedIn.