In this final chapter, we will discuss high-performance computing techniques for large computational biology datasets. We will talk about code parallelization, running software in clusters, code optimization, and advanced functional programming techniques. We will try to avoid tying any solution to a specific proprietary technology (for example, Amazon EC2) and design code that can be applicable in a wide range of scenarios.

The whole topic of persistence is mostly left out of this chapter, although we do make some minor considerations on the IO performance. There is no single good solution for persistence in computational biology; you will probably use SQL datasets for some limited applications. Most of your files will be BAM- or VCF-formatted, and you will probably use a lot of text files too. You may also want to consider NoSQL databases in some instances. Having said that, if you have not checked HDF5, you may want to have a look at it, especially as there are quite a few...