<p>Hello everyone,</p>

<p>Today I spent 4 hours on a python script for executing a shell command constructed using user inputs within the script, still It was unsatisfactory to what I wanted. I achieved same thing using R &lt; 30 mins. I am in under obsession that one of the scripting language is very important. I use R, shell and terminal utilities for most of my tasks. </p>

<p>So, the argument would be I haven't come across to such a task in exploratory next generation sequencing data analysis, where you specifically need a scripting language like Perl/Python or Ruby.</p>

<p>Thus, if one is not writing new tools from scratch, how important is to learn any of the scripting language. I used Perl in start and then got influenced by python co-workers that python is better and more extensive and now lost in both. But I am confident in R.</p>

<p>Could someone also elaborate, the part and parcel of work, where there is no move without any of the scripting language. One can also argue about the audience, perl user , python and R users at the consumer end, if you make software but what if the results and tasks are for oneself or its just a matter of taste.</p>

<p>Thanks for your input</p>

<p>From a certain point of view you are right: you don't need to learn python or perl programming, and you can do a lot of work just in R. CRAN and Bioconducator contain a lot of libraries, and R allows you to create good plots, which is one of the most important skills for a bioinformatician. I know people who mostly use only R, and they are very good in their work, so you don't have to be afraid if you don't want to learn other programming languages.</p>

<p>However, consider that learning at least the basics of other languages does not take too much time, adds skills to your curriculum, and allows you to learn new approaches to programming. R is a language for data analysis, centered on the data.frame structure, and is suited mostly to analyze data organized in tabular form. That's a good paradigm for analysing data, but as soon as you have to other problems R becomes more clunky and less useful. Web programming is an example, but also data manipulation (convert one format to another, automatizing tasks on the shell, etc.) is important. If you know the philosophy under which other programming languages are developed, and what tasks are they typically used for, your programming skills will be stronger, and you will be able to choose among a larger range of approaches when you have to solve a certain programming topic.</p>
