Metadata-Version: 1.1
Name: tmtk
Version: 0.1.2
Summary: A toolkit for ETL curation for the tranSMART data warehouse.
Home-page: https://www.github.com/thehyve/tmtk/
Author: Jochem Bijlard
Author-email: j.bijlard@gmail.com
License: UNKNOWN
Download-URL: https://github.com/thehyve/tmtk/tarball/0.1.2/
Description: ====
        tmtk
        ====
        
        A toolkit for ETL curation for the tranSMART data warehouse. The
        TranSMART curation toolkit (``tmtk``) can be used to edit and validate
        studies prior to loading them with `transmart-batch`_.
        
        Some features: 
         - create a transmart-batch ready study from clinical data files.
         - load an existing study and validate its contents. 
         - edit the transmart concept tree in The Arborist graphical editor. 
         - create chromosomal region annotation files.
        
        Disclaimer
                  
        
        tmtk is a ``python3`` package meant to be run in ``Jupyter notebooks``.
        Results for other setups may vary.
        
        Usage
        -----
        
        Step 1: Opening a notebook
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        First open a Jupyter Notebook, open a shell and change directory to some
        place where your data is. Then start the notebook server:
        
        .. code:: sh
        
            cd /path/to/studies/
            jupyter notebook
        
        This should open your browser to Jupyters file browser, create a new
        notebook for here.
        
        Step 2: Using tmtk
        ^^^^^^^^^^^^^^^^^^
        
        .. code:: py
        
            # First import the toolkit into your environment
            import tmtk
        
            # Then create a <tmtk.Study> object by pointing to study.params of a transmart-batch study
            study = tmtk.Study('~/studies/a_tm_batch_ready_study/study.params')
            # Or, by using the study wizard on a directory with correctly structured, clinical data files.
            # (Visit the transmart-batch documentation to find out what is expected.)
            study = tmtk.wizard.create_study('~/studies/dir_with_some_clinical_data_files/')
        
        Now we have loaded the study as a ``tmtk.Study`` object we have some
        interesting functions available:
        
        .. code:: py
        
            # Check whether transmart-batch will find any issues with the way your study is setup
            study.validate_all()
        
            # Graphically manipulate the concept tree in this study by using The Arborist
            study.call_boris()
        
        For more, see the `examples`_.
        
        Installation
        ------------
        
        To install tmtk, and all dependencies, into your Python environment run:
        
        .. code:: sh
        
            $   python3 setup.py install
        
        or if you want to run the tool from code:
        
        .. code:: sh
        
            $   python3 setup.py develop
        
        Requirements
        ^^^^^^^^^^^^
        
        These dependencies will have to be installed:
         - pandas
         - jupyter
         - flask
         - ipython
         - tqdm
         - requests
         - rpy2
        
        Licence
        -------
        GPLv3
        
        Authors
        -------
        
        .. _transmart-batch: https://github.com/thehyve/transmart-batch/
        .. _examples: examples
Keywords: transmart,etl,arborist,concept tree
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
