2009 post: Key Bioinformatics Computer Skills

Note: this was written in 2009 so… out of date somewhat!

I’ve been asked several times about which computer skills are critical for bioinformatics. Important – note that I am just addressing the “computer skills” side of things here. This is my list for being a functional, comfortable bioinformatician.

  1. SQL and knowledge of databases. I always recommend that people start with MySQL, because it is crossplatform, very popular, and extremely well developed.
  2. Perl or Python. Python wins now! (2017 update!)  Preferably perl. It kills me to write this, because I like python so much more than perl, but from a “getting the most useful skills” perspective, I think you have to choose perl.
  3. basic Linux. Actually, being at a semi-sys admin level is even better. I always tell people to go “cold turkey” and just install Linux on their computer and commit to using it exclusively for a while. (Due to OpenOffice etc, this should be mostly doable these days). This will force a person to get comfortable. Learning to use a Mac from the command line is an ok second option, as is Solaris etc. Still, I’d have to say Linux would be preferred.
  4. basic bash shell scripting. There are still too many cases where this ends up being “just the thing to do”. And of course, this all applies to Mac.
  5. Some experience with Java or other “traditional languages” or a real understanding of  modern programming paradigms. This may seem lame or vague. But it is important to understand how traditional programming languages approach problems. At minimum, this ensures some exposure to concepts like object-oriented programming, functional programming, libraries, etc. I know that one can get all of this with python and, yes, even perl – but I fear that some many bioinformatics people get away without knowing these things to their detriment.
  6. R + Bioconductor. So many great packages in Bioconductor. Comfort with R can solve a lot of problems quickly. R is only growing; if I could buy stock in R, I would!

This may seem like a lot, but many of these items fit together very well. For example, one could go “cold turkey” and just use Linux and commit to doing bioinformatics by using a combination of R, perl and shell scripting, and an SQL-based database (MySQL). It is very common in bioinformatics to link these pieces, so… not so bad, in the end, I think.

As always, comments welcome…

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