Inspired by the awesome Hilary Parker and the dawn of a new academic year, I’ve put together a rundown of tools I find essential in my day-to-day as a biostatistics graduate student. None of this was formally taught to me – much has been recommended, learned on the fly, or found via the “just Google it” method – but I hope to inject some sense of coherence into the whole situation with this post. We thought something like this would be especially useful for incoming students or anybody looking to change or optimize their setup. So let’s begin!
My personal computer is a 15″ MacBook Pro, which I got in October 2011. I was hesitant to make the switch over to the Mac (I had owned only PCs before then), but I’ve never been happier with a laptop. The work I do on a daily basis is much better streamlined on the Mac. However, either platform works in our field, so I’ll be sure to note when a piece of software I discuss is Mac- or PC-specific. The laptop is my main piece of hardware (not counting our departmental computing cluster, which I’ll mention later) – the only other thing I’d mention is my 300GB external hard drive, which I use to back up my computer with Time Machine. Backups are absolutely essential – I choose to use an external drive, but backing things up in the cloud has become common practice. I use Dropbox (you get 2GB for free) for backing up my most important files and for creating shared folders. Other common cloud storage solutions are Amazon S3 and SugarSync.
By far, my favorite piece of software is R – every statistician’s best friend. It rocks. In the genomics world, most R packages are published on Bioconductor. The R GUI on the Mac is pretty awesome, so working with R and Bioconductor locally required almost no setup for me.
What was a bit more challenging was figuring out my R situation when working on our departmental computing cluster – i.e., when working on a remote machine that I’ve logged into from my laptop via ssh. There are two pieces of software I’ve found really useful when working remotely: Cyberduck (for file transfers) and Aquamacs (for running code interactively from my machine to the cluster – Mac-specific). I’m not fully convinced that Aquamacs is the best way to go for the interactive code – in fact, the thing I miss most about having a PC is the text editor Notepad++. Notepad++ is a PC-specific editor that connects beautifully to R (with NppToR – just hit F8 to run a line in R locally!) or to an ssh client (just hit F9 to run a line remotely!). However, I have a pretty good system worked out using Aquamacs and ESS – I’ll post the specifics in another post. And, speaking of text editors – I’ve come to like TextWrangler (Mac-specific) quite a bit.
For typesetting anything with more than one equation in it, I (and most of the mathematical/statistical community) use LaTeX. I use TeXShop as my frontend and MacTeX as my TeX distribution. This setup works like a dream on my Mac – it’s incredibly fast, and it took NO customization to get the two features that are really important to me: (1) automatic PDF refresh when you change your TeX code and (2) a backward search feature where I can click on the PDF and be taken directly to that point in the TeX code. When I used a PC, I used TeXnicCenter as my frontend and MiKTeX as my TeX distribution, but I also found that I needed Sumatra (an alternative to Adobe for reading PDFs) and some extra customization to get my two required features.
I use PowerPoint for presentations containing zero or one equation(s), and I use Beamer (a LaTeX class) for anything with two or more equations. I have PowerPoint 2008, which is pretty slow on a Mac, so I’ve been considering trying Keynote. (Thoughts, anyone?). I’ve also tried to get the best of both the PowerPoint and Beamer worlds (WYSIWYG + nice equations) by using LaTeXiT. There’s a PC-equivalent called Aurora, which I used once for 30 days until my free trial expired.
That’s pretty much all I use on a daily basis. I’ll mention a couple other miscellaneous things: I’m just starting to use github to manage and share my code – git has great mechanisms for keeping track of all the craziness that comes with doing a shared project. Lots of people in my department use Sweave, a cool way to integrate R and LaTeX. I am not one of those people. Sweave is especially good for putting together manuals, but not so good for working with analyses that take a while to run or that need to be very specifically formatted.
I’d love to hear about any setup tips that you find useful – do share!