Some time ago Abel wrote about how to identify cancer drivers from tumor somatic mutations, and presented OncodriveFM. Nuria also posted a nice poster explaining it together with TransFIC.
Initially, OncodriveFM was written by Abel as a Perl script and distributed through our web. Later on I had to implement the analysis workflows of IntOGen SM, which required to use it intensively. However,
we realized that the code of OncodriveFM could be significantly improved in terms of performance, as there is a part of the analysis that may take quite a lot of time depending on the input data. This is why I decided to implement it again, starting from a prototype written by Abel, using Python.
This new release 0.3.2 has been extensively validated to check that the results match those of the original implementation, and includes some important optimizations. The first is the use of NumPy for internal data representation and calculations, and the second is the possibility to use multi-core processors to run the most expensive part in parallel. Moreover, the command line interface has been improved, and now is quite flexible and easy to use.
This new OncodriveFM depends on numerical Python libraries (numpy, scipy, statsmodels) that have to be installed previously in order to work. There is a detailed documentation in the Bitbucket repository that specifies how to install the dependencies, how to download and install OncodriveFM, and how to run the included example.
We encourage you to use the Bitbucket issue system to ask for features or report errors.