<p>As a bioinformatics team grows there is huge benefit from sharing code, particularly with strong coding guidelines that promote read-ability and reuse.</p>

<p>But can we really pick common technology, infrastructures shared with our colleagues? Generic scripting languages like PERL, Python and Groovy are great, and each come with different strengths for common file and data marshalling or common mathematically/statically data field manipulations. </p>

<p>Other less generic tools, like R, KNIME, Galaxy take us down deeper applications for data analysis without becoming science application specific.  And often it is specific tools for the instrumentation that is more efficient for targeted work.  What is a bioinformatics team to do?</p>

<p>Thoughts? </p>

<p>Use the best tool for the job? Have people around that know Perl or Python and R, are very efficient under Linux and can learn to use new tools fast. The problems that are found within the field of bioinformatics are very diversified and you won't come close to anything that could be regarded as 'the best generic scripting tool'. Cheers</p>