You don't want to hear this, but....

Sometimes you have so much data, that even iPlant can only help you just so much... then you have to start learning how to actually run some of the tools directly on the command line on a Linux machine. This may come up when your RNA-Seq project includes 20 or 30 paired-end sequence files. Maybe there is 200 GB or more data, or maybe your files are big-- 25-30 GB each. It's not that iPlant can't help, but your analysis may just work better – faster and with less wasted computational time, if you can run some of the jobs directly or if you learn to use a workflow manager. Keep in mind that one of the most valuable tools iPlant provides is the Data Store, which gives you a place to store your files, and helps you move them around – not just for the Discovery Environment, but also for Atmosphere (https://atmo.iplantcollaborative.org/application), which can provide you your own Linux machine to work with using the GUI or the command line. You can also readily move your files to XSEDE (https://www.xsede.org) supercomputing systems, such as the ones at TACC (https://www.tacc.utexas.edu). Learn some command-line skills and you could be using a supercomputer to analyze your big batch of data. iPlant works with TACC in providing access to their large systems in multiple ways. We try to make it easier for you to get started with working with command line skills, and to use the right software, in the appropriate environment.

Getting Started

There are many places on the web that will help you get started with command line Linux. If you are at a university, there are probably some classes or seminars for this. But there are lots of tutorials and teaching aids just on the web for free: