So, you will probably hate me for asking this question here, as there are lot of forum and blog posts on internet about it and it is also a very subjective question.

However, it may be a starting point for a good discussion, if we don't flame... Which operating system do you usually use for your work? Did you install it by yourself, and do you have administrative rights on it, or is there any IT administrator in your lab?

I have no experience with them, but there are several Linux distributions out there that come preloaded with bioinformatics software.

For example:

• biobuntu which comes preloaded with amapalign, biococoa, biomode, bioperl, biopython, biosquid, blast2, boxshade, chemtool, clustalw, clustalx, dialign, easychem, fastdnaml, fastlink, garlic, gchempaint, gcubin, gff2aplot, gff2ps, EMBOSS, gmt, gromacs, hmmer, ifeffit, ifrit, imview, kalign, leksbot, libbioruby, meltinggui, mipe, molphy, mozillabiofox, mpqc/support, mummer, muscle, mustang, ncbiepcr, ncbitoolsbin, ncbitoolsx11, njplot, openbabel, perlprimer, phylip, poa, polyxmass, primer3, probcons, proda, pybliographerA, rasmol, readseq, seaview, sibsim4, sigmaalignSimple, sim4, SixpackDisplay, tcoffeeMultiple, tigrglimmerGene, treepuzzleReconstruction, treetool, treeviewxDisplays, viewmol, wise, xbs, xdrawchem and xmakemol

• Bio-Linux a fully featured, powerful, configurable and easy to maintain bioinformatics workstation. Bio-Linux provides more than 500 bioinformatics programs on an Ubuntu Linux base. There is a graphical menu for bioinformatics programs, as well as easy access to the Bio-Linux bioinformatics documentation system and sample data useful for testing programs. You can also install Bio-Linux packages to handle new generation sequence data types.

• The vision for Cloud BioLinux is to offer a base image of genome analysis resources for cloud computing platforms, such as Amazon EC2. This Science as a Service model (ScaaS) will allow us to incorporate, develop and optimize life science software as well as supporting data sets on compute clouds. This project is driven by the observation that commonly-used bioinformatics tools are hard to build and maintain, require high amounts of resources, or just too numerous to choose from.

• BioBrew is a collection of open-source applications for life scientists and an in-house project at Bioinformatics.Org. The BioBrew Roll for Rocks can be used to create Rocks/BioBrew Linux, a distribution customized for both cluster and bioinformatics computing: it automates cluster installation, includes all the HPC software a cluster enthusiast needs, and contains popular bioinformatics applications.

• Debian Med is a "Debian Pure Blend" with the aim to develop Debian into an operating system that is particularly well fit for the requirements for medical practice and research. The goal of Debian Med is a complete system for all tasks in medical care which is built completely on free software.

All of the 3 major platforms have their advantages, and I use all 3 practically every day. Mac OS X is my primary desktop OS, for a number of reasons, but mostly because I just seem more productive using it than any of the alternatives. All of my coding work is done over SSH on Linux (almost exclusively Ubuntu) servers. The power of Aptitude package management, and the robustness of this platform means that there really is no other choice for this kind of work. Finally I run Windows 7 on my netbook, because it is an excellent OS for that platform, and enables me to do everything I want that machine to be capable of, note-taking, blog writing, as a display machine for Powerpoint etc. It is also useful to have Internet Explorer kicking around somewhere for compatability testing.

I wouldn't consider using any machine that I didn't have admin rights on for work purposes, if I have to jump through hoops to get stuff installed, it just slows me down too much. This is another reason for using OS X for my primary desktop, it allows me to escape the University's "Common Desktop" policy for Windows PCs, which would take control of my computer out of my hands.

Highly subjective answer of course, but I don't think you can go wrong with Linux at the backend. In general, you will find a vast variety of software, great community support, better work/$ numbers at scale. I tend to prefer debian-based distro's (Ubuntu, Debian, etc) but that's a personal choice. On the front end, I've successfully used IRIX (dating myself), Ubuntu, and OSX.

Tips for installing software om Max OS X:

• install the Apple developer tools called Xcode http://developer.apple.com/tools/xcode/
• install MacPorts from http://www.macports.org/

You can now easily install everything from command line using the port command. List all available software

port list

Install libraries and software. etc:

port install <some-library>

In my Master's in Bioinformatics I used RedHat 7-8 and first edition of Fedora, then for the first two years of my PhD I continued with Fedora, then moved to Ubuntu and For servers to host I used RHEL earlier and now CentOS and Ubuntu server edition. I strongly vote for Ubuntu distro for it's ease of use and strong community presence.

In my group, all primary computational folks (currently, a new person will be bucking this trend and going with OSX) have linux desktops that they have root access to. Most of us have a secondary machine which varies between windows & Mac OSX for various side tasks. Beyond that we have several linux based servers that people use as well (via SSH). The very few people who do any sort of computational work w/o a linux desktop ssh into these servers to do all of their real work.

My tip: install Cygwin if you are using Windows

I have a Mac Pro dual quad core that I use for everything. I use the Mac OS for day to day email, most graphics, browsing, I run a VMWare virtual Windows machine, and I do most analysis in the unix terminal. Windows runs much better on the Mac hardware, Excel is much faster in Window, and I can fileshare between the Windows and Mac systems. So far this has been sufficient for me. If I run into a situation where I need more computing power, I can ssh to a Linux server, but I haven't needed to yet. I configured the machine with 16 GB RAM, leaving slots open to add another 16 if needed. I've been happy with this.

Often people are limited to their choices by factors outside of their control. One lab that I work with requires the use of Mac computers another is using Windows mostly. Large scale computations seem to be best suited for Linux systems.

Luckily there is a migration towards unified capabilities across all platforms. Installing Cygwin on Windows allows us to tap into the power of Unix, while Linux distros have advanced graphical user interfaces like Windows and Macs.

From my own observations of non technical people, the installation of new and interdependent software packages seems to be the most difficult on Mac computers and easiest on Windows due to the computational architecture that makes all Windows computers identical.