Chapter 16 Continuing on your own

After this workshop you will not have access to the RStudio server. To continue working on your research you will need access to some of the software. Options for installation are provided within the chapters.

If you continue to work with target-capture data such as we provided for this workshop, you may be sequencing much larger datasets than our examples (which included low-coverage subsets). There are several options for working with large datasets that are beyond the capacity of your personal computer. First, you can check whether you have access to a larger workstation computer through your university. This computer will likely function much like the server we have used here, but will have additional storage as well as computing power. You may have access to a high-performance computer cluster (HPC) through a university. This option will have storage as well as computing power, which may be shared across the university.

A third option for researchers without the ability to purchase a large (possibly shared) computing resource is to use shared resources via the cloud. A great set of instructions for setting up a cloud server is https://deanattali.com/2015/05/09/setup-rstudio-shiny-server-digital-ocean/ . While on first glance this option may appear very expensive, if you plan to use a large server for a few days only, you can spend a relatively small amount of money and then reduce the computing power of the droplet to a minimal charge per day while allowing you to continue to work with your results. Alternatively, you may “snapshot” all of your information (i.e. keep it on a disk) and shut down the server to incur only storage costs. See https://docs.digitalocean.com/products/droplets/how-to/resize/. While DigitalOcean is given as the example here, Google also has cloud services that operate similarly.