Welcome to the first installment of How Molecular Ecologists Work! This entry is from Dr. Brant Faircloth, assistant professor of computational biology at Louisiana State University. Brant’s work broadly revolves around elucidating the factors that shape biological diversity. In practice, he spends a great amount of time developing new molecular and computational tools to help scientists understand the evolutionary history of non-model organisms.
Location: Louisiana State University, Baton Rouge, LA
Position: Assistant Professor (of Computational Biology)
Current mobile device(s): iPhone 6 (iOS 9); iPad Pro 9.7” (iOS 9)
Current computer(s):
- iMac 27” Retina 5k, 3.5 Ghz CPUs, 32 GB RAM
- Mac Book Pro 13” Retina, 2.9 Ghz CPUs, 16 GB RAM
- Supermicro SuperServer 5017R-MTF; Dual Xeon CPUs; 12 cores total; 48 GB RAM; CentOS (quantity 2)
- Supermicro SuperServer 6017R-WRF; Dual Xeon CPUs; 12 cores total; 64 GB RAM; CentOS (quantity 2)
- Synology DS1813+ DiskStations with ~15 TB current storage (quantity 2 – one backs up to the other)
- SupermikeII – 146 TFlops supercomputer (http://www.hpc.lsu.edu/docs/guides.php?system=SuperMike2)
- Supermic – 557 Tflops supercomputer (http://www.hpc.lsu.edu/docs/guides.php?system=SuperMIC)
- QB2 – 1052 Tflops supercomputer (http://www.hpc.lsu.edu/docs/guides.php?system=QB2)
What kind of research do you?
My group is interested in understanding those factors (evolutionary and ecological) that are responsible for generating and maintaining biodiversity. And, right now, we’re leaning more heavily towards our interests in the evolutionary events that influence the generation of diversity. Practically, that means we work with many non-model organisms, so we also do a fair amount of methods development (both computational and molecular) to help us collect genome-scale or genomic data from our organismal group(s) of interest.
The tools that we use (or develop) as part of our work include more traditional ecological data and sample collection techniques (including specimens from museum collections – and an enormous thank you to everyone working to maintain and improve these collections) as well as a number of current sequencing techniques, including genome sequencing, amplicon sequencing, RAD-seq, targeted sequencing, and transcriptome sequencing. To meld all of these together, we do a fair amount of computational work – from writing our own analysis software to implementing and scaling up the excellent software from other groups.
Can you use one word to describe the way you work?
Efficiently. Well, that sounds snotty. I try to work efficiently – with varying degrees of success, and I try to find new ways to be more efficient. The efficiency angle is part of my attempt to maintain my sanity and happiness in this job (which I love – and which I would love much less if it was making me crazy).
Being as efficient as possible means that I can (usually) work regular hours and avoid working on the weekends. I take that time to enjoy my life and have fun with my friends. This sets up a useful feedback loop, because being well-rested and happy lets me be more efficient when I come back to work on Monday.
What specific strategies do you recommend for running (or establishing) a lab?
Be nice. Be open. Be honest. Be persistent.
There are a lot of really nice, really cool, really awesome scientists out there. Work with them, spend time with them, model their actions. Try to be like them or incorporate aspects of their shop to yours. But, also try to find new and interesting ways to be little bit better – all while remaining nice, open, and honest.
The other important bit is not to get frustrated (something that I work on a lot) – sometimes it’s people you have to deal with who are not very nice or open or honest, and other times it’s just the grind of dealing with grant writing, manuscript writing, etc. Persistence and a positive outlook go a hell of a long way towards mitigating the frustration. And, again, being able to take a break from work on the weekends really, really helps.
What apps/software/language/tools can’t you work without (Python, Dropbox, Geneious, etc.)?
Well, we write most of our code in Python, and it’s a pleasant language to work with (and learn), so it’s up there as an important tool. That said, I would probably say that the three most important tools that I use are my terminal/shell, my text editor, and Dropbox.
As you’ll see below, I spend a lot of time in the terminal, so having a properly configured terminal and shell are pretty important to me. On that front, I use iTerm as my terminal of choice and I use zsh as my shell of choice. Within zsh, I use prezto, which is a reasonably straightforward way to configure zsh to do lot of helpful things (like excellent history search, pleasant colorization, etc). I also prefer the zsh mode of scripting (to that of bash).
For my text editor, I’m really pleased with sublime text, although I also use vim. Many people have their favorites, and sublime text is mine – it’s configurable, fast, pretty, and easy to use/customize.
Dropbox is, to me, probably the biggest workflow-changer. I maintain all of my “normal” directories and files in Dropbox – meaning that I don’t have any “normal” files/directories that are not synced across machines. This excludes all of our larger, “non-normal” sequence/analysis files, which we maintain on a network filesystem machine (NFS), but otherwise means that I have a copy of everything, everywhere, whenever I need it.
Where do you work with data (personal computer, lab computers, cluster, etc.)?
I usually work on my iMac with our personal servers (SuperMicro machines, above) over an ssh session in the terminal. We use these server machines, which are reasonably well provisioned, for initial data processing, and then we move the files we prepare for analysis over to the really big machines that the university cares for (the HPC staff at LSU are among the best I’ve worked with and care for and maintain some damn big iron). This workflow gives us a bit more freedom to install what we need on our servers, frees up the supercomputers for the analyses they were meant for, and gives us lots of options, in-between.
Besides your phone and computer, what gadget can’t you live without and why?
Headphones. I have a pair of reasonably priced, studio headphones (Sony MDR-7506). Paired with a standing desk, the damn things are so good that I commonly find myself dancing in the office. It’s basically workday Jazzercise in here. Every. Day. I usually keep my door closed for this reason.
Can you estimate what percentage of time you spend on the following categories in a given week?
These are pretty variable in any given week. I’ll give it a shot, but the categories change a lot depending on the time of the year, so I’ve tried to (mentally) average things out:
15% Research-grant writing
20% Research-manuscript writing
10% Research-in the Lab, analyzing data, in the field
30% Teaching
20% Meetings/Email (committees, project meetings, etc.)
5% Outreach
What is your best time-saving shortcut/lifehack?
Learn your tools. Know them well. Be cautious of switching, but don’t be afraid to assess new tools (in cursory fashion) and make the switch when/if the benefits overwhelm the costs.
How do you stay organized (to-do lists, digital reminders, etc.)?
I’d like to have something life-changing to offer here, but I use a pretty ad-hoc system that revolves largely around my email and mental list of things that need doing. David Allen (GTD guru) would be displeased if he read this last statement.
I would like to find some sort of task management approach that really works for me, and this is one of those tools that I’m constantly assessing and have not yet identified/mastered. My inability to commit to certain approaches (like Allen’s GTD and/or some software like Omnifocus) is that it always seems to me that you end up spending more time managing your damn tasks than just going ahead and doing them.
What do you listen to while you’re working (music, kids yelling, the hum of a supercomputer)?
Music. Lots of music. For coding purposes, usually something electronic(-ish). I’m currently listening to the Chill Tracks playlist on Spotify. I also have a couple of heavily curated playlists of my own, and I listen to those a lot. Sometimes, when I’m writing, I listen to classical. And, sometimes when I’m revising/rebutting, I listen to hip-hop. It’s cathartic.
What are you currently reading?
I just finished “Ready Player One” (enjoyed it – it’s 80s pop-culture nirvana) and have moved on to “A Brief History of Seven Killings”.
What is your sleep routine like?
Sleep is important. I’m good at it, and I enjoy it. I usually go to sleep around 11:30 and get up around 6:30. I’m not much of a napper.
Fill in the blank: I’d like to see _______ answer these questions.
Hmm. How about Corrie Moreau?
What career advice would you like to give to our readers?
Be nice. Be open. Be honest. Be persistent. Learn your tools. Listen to music. Enjoy your life and you will enjoy your job. Have fun.
Thanks Brant! Up next: J. Chris Pires