This release of g:Profiler embodies an extensive update on both the back and front end. The core parts of the toolset have been revised and rewritten in order to keep up with the modern development trends and to speed up calculations. The back end is now reimplemented in Python 3.6 employing the widely used packages such as numpy, pandas, scipy and statsmodels. The biggest change in the back end lies in the data structure for keeping and accessing the annotations. We replaced the previous BerkeleyDB engine with SQLite database and utilised the Roaring bitmaps (32) data structure resulting in faster set operations.
