BOL

I recommend USA. Study bioinformatics in U.S. universities and colleges may differ from those in your home country in several ways. For one thing, competative research lab, small class sizes are very common. There may be as few as 10 to 20 students in a class, giving you the personal attention you need in order to succeed. While in class, students are encouraged and expected to contribute to the discussion. Studying in the U.S. gives you the opportunity to gain a mentor in your given career field, an invaluable resource.

I recommend USA. Study bioinformatics in U.S. universities and colleges may differ from those in your home country in several ways. For one thing, competative research lab, small class sizes are very common. There may be as few as 10 to 20 students in a class, giving you the personal attention you need in order to succeed. While in class, students are encouraged and expected to contribute to the discussion. Studying in the U.S. gives you the opportunity to gain a mentor in your given career field, an invaluable resource.

RStudio v0.99.292 Preview — Release Notes

A preview release of RStudio v0.99.292 is now available for testing and feedback. Highlights include:

• Data viewer with support for large datasets, filtering, searching, and sorting.
• Complete overhaul of R code completion with many new features and capabilities.
• C/C++ editing mode: completion, code navigation, find usages, and automatic indentation.
• Source editor improvements including multiple cursors, tab re-ordering, and several new themes.
• Enhanced Vim mode with visual block selection, macros, marks, and subset of : commands.
• Updated UI rendering engine for improved overall responsiveness.

See v0.99.292 Release Notes for full details on all of the changes in this release.

More at http://www.rstudio.com/products/rstudio/download/preview/

R is an exceptionally powerful language in manipulation and transformation of data, statistical analysis and graphics. It doesn have support for the wide array of statistical functionality. So in my opinion R is great if all you're doing is statistics. It's got a nice interactive interface and visualization tools.

R discussion http://bioinformaticsonline.com/discussion/view/119/which-are-the-best-statistical-programming-languages-to-study-for-a-bioinformatician

You can also found several other material at http://bioinformaticsonline.com/groups/profile/93/r-and-bioconductor

My vote goes to R (http://cran.at.r-project.org) environment is an easy to use and write programs and custom functions. The R programming syntax is extremely easy to learn, even for users with no previous programming experience.

R has also quickly found a following because statisticians, engineers and scientists without computer programming skills find it easy to use. R is really important to the point that it’s hard to overvalue it and also allows statisticians to do very intricate and complicated analyses without knowing the blood and guts of computing systems. Therefore, my vote goes to R.