Bioinformatics Zen

One of the things I’ve found in two years of doing bioinformatics, is that directories quickly fill up with files, usually data, scripts, and results. Working out the contents of each file is difficult as the only identifier is the name, which with lots of similarly named files, is confusing. Using lots of scripts gets more complicated when there are dependencies. For example scripts need the data from one file, or are dependent on an intermediate set of results from the output of another script. These dependencies mean that when a set of results needs updating, usually many times when producing a manuscript, scripts need to be re-run in the correct order. The requirement of manually re-running scripts in a specific order is cumbersome, and easily generates errors.

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Coding is fact of life for bioinformatics. If you work in bioinformatics you probably enjoy coding to some extent. It’s our equivalent to PCR, western blots and sequencing. So whether your weapon of choice is Java, Perl, Python or C++, here’s three packages and a tool worth a look.

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Previously, I wrote about organising your file system to make the relationships between files that produce data, and files containing data more descriptive. One of the best tips I’ve been given, is to store all my data in a database. Regardless of what the data is, or how “mission critical”. Here are some reasons to use a database, rather than files, to store your data.

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