Major bioinformatic software tools that we develop include:
Software development approaches
We believe in Reproducible Research & Software Sustainability. When possible we respect style guides and use unit testing & continuous integration. We aim to respect these approaches in our research on specific biological questions and in our tool development. We develop mostly in:
- R for number crunching.
- Shell for minimalisting pipelining.
- Python or ruby when text needs to be analysed.
- But also use bash/python/perl when convenient or necessary...
But we love quick and dirty hacks too .
A lot of our code is at https://github.com/wurmlab.
Some tools now have limited relevance
oSwitch has been superceded by updates in docker. Afra has been used in our MSc course; it is currently somewhat out of sync with main Apollo.