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Why R?
In contrast to the calculators, doing small calculations on computers usually required quite a bit of effort in the earlier days. The scientist had to code his question in a high-level programming language (FORTRAN or C), compile it and execute it with necessary parameters. Only then, he could see the desired results. Compilation could fail due to syntax errors, no matter how simple or complex the question was. The requirement to code was a big road-block preventing efficient use of computers.
R created a software environment to allow scientists to run interactive calculations, thus eliminating the need to write programs in high-level languages. Mathematica and Matlab allowed the same thing, but R came with the added advantage of being open-source and completely free.
R is designed for mathematical calculations.
R is a very powerful software tool for analysis of biological data. It is an excellent choice for biologists reaching the limits of Excel, because learning R is quite easy. The learning curve is minimal for Matlab or Mathematica users, and R comes with an added benefit of costing less than a cup of coffee. In fact, it costs less than the paper napkin to wipe coffee table. R is free. Primarily for that reason, many users have contributed powerful libraries to R. Those libraries can make statistical analysis of bioinformatic data straightforward. We are particularly attracted to Bioconductor suite of packages.
Advantages
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Small learning curve
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object-oriented language
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publication quality images
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free and open source
