Lincoln Stein lays out “The case for cloud computing in genome informatics” pretty nicely. The article describes the inflection point of sequencing technology. That is from 1990 to 2004 ‘base-pair/$’ doubled every 19 months versus a doubling every 5 months since 2004 to present. There is no end in sight.
Moving data to the cloud remains the biggest obstacle to cloud adoption. The article makes the case for moving the computation to the data instead of vice versa. Presupposing however that people will be willing to move their data at least 1 time. Otherwise, “moving the computation to the data” is an argument for building and maintaining a local compute cluster, nearby the sequencing instrument.
At GQ we realize there is no “one size fits all”. We support a hosted, cloud based solution for customers with limited IT expertise or inclination. Or, for lab operations running multiple sequencing instruments, we can install the cloud locally so you benefit from the bandwidth of the Local Area Network connecting the instrument to computing. Either way, data moves only 1 time and GQ solves for scalability with its algorithms and data model.
