Mantis-ml

Major

- Add option for 'fast' run (`-f / --fast`) with 4 ML models (instead of the default 6 models)

- Add option (`-m`) to explicitly specify the supervised models to be trained by mantis-ml.
Available model options are:
- _et_: Extra Trees
- _rf_: Random Forest
- _gb_: Gradient Boosting
- _xgb_: XGBoost
- _svc_: Support Vector Classifier
- _dnn_: Deep Neural Net
- _stack_: Stacking classifier

Multiple models may be specified using a ',' separator, e.g. `-m et,rf,stack`

- Stacking classifier may now be run using the `-m` option with the `stack` arg, i.e.: `-m stack`

Minor
- Fix bug in `hypergeom_enrichment` module when reading external ranked files (only tab-delimiter is currently allowed in case of an external file with two columns)

- Streamlined installation with "python setup.py install"
- Tool now available at PyPI and can be installed through pip
- The tool now offers three executable scripts to run from the command line (mantisml, mantisml-profiler and mantisml-overlap)
- The user can define their own output folder via the -o option
- Config input parameters have been drastically simplified: a lot of the underlying complexity has been hidden to the end user and only required input is disease/phenotype-associated terms in free text
- The mantisml-overlap script is a new addition to the tool as it packages the enrichment test functionality between mantis-ml predictions and any external ranked gene list that is provided by the user