The old genome informatics ecosystem. Under the traditional flow of genome information, sequencing laboratories transmit raw and interpreted sequencing information across the internet to one of several sequencing archives. This information is accessed either directly by casual users or indirectly via a website run by one of the value-added genome integrators. Power users typically download large datasets from the archives onto their local compute clusters for computationally intensive number crunching. Under this model, the sequencing archives, value-added integrators and power users all maintain their own compute and storage clusters and keep local copies of the sequencing datasets.

Historical trends in storage prices versus DNA sequencing costs. The blue squares describe the historic cost of disk prices in megabytes per US dollar. The long-term trend (blue line, which is a straight line here because the plot is logarithmic) shows exponential growth in storage per dollar with a doubling time of roughly 1.5 years. The cost of DNA sequencing, expressed in base pairs per dollar, is shown by the red triangles. It follows an exponential curve (yellow line) with a doubling time slightly slower than disk storage until 2004, when next generation sequencing (NGS) causes an inflection in the curve to a doubling time of less than 6 months (red line). These curves are not corrected for inflation or for the 'fully loaded' cost of sequencing and disk storage, which would include personnel costs, depreciation and overhead.

The 'new' genome informatics ecosystem based on cloud computing. In this model, the community's storage and compute resources are co-located in a 'cloud' maintained by a large service provider. The sequence archives and value-added integrators maintain servers and storage systems within the cloud, and use more or less capacity as needed for daily and seasonal fluctuations in usage. Casual users continue to access the data via the websites of the archives and integrators, but power users now have the option of creating virtual on-demand compute clusters within the cloud, which have direct access to the sequencing datasets.