tmtk - TranSMART data curation toolkit¶
|Generated:||Oct 17, 2019|
A toolkit for ETL curation for the tranSMART data warehouse for translational research.
The TranSMART curation toolkit (
tmtk) aims to provide a language
and set of classes for describing data to be uploaded to tranSMART.
The toolkit can be used to edit and validate studies prior
to loading them with transmart-batch.
- Functionality currently available:
- 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.
- map HGNC gene symbols to corresponding Entrez gene IDs using mygene.info.
tmtk is a
python3 package meant to be run in
Jupyter notebooks. Results
for other setups may vary.
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:
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¶
# 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:
# 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()
- User examples
- Data formats overview
- API Description
- Data templates
- Wibo Pipping
- Stefan Payrable
- Ward Weistra