pathway induced multiple kernel learning for computational biology
- Free software: MIT license
- Documentation: https://pimkl.readthedocs.io.
The pimkl command:
Usage: pimkl [OPTIONS] NETWORK_CSV_FILE NETWORK_NAME GENE_SETS_GMT_FILE
GENE_SETS_NAME PREPROCESS_DIR OUTPUT_DIR CLASS_LABEL_FILE [LAM]
[K] [NUMBER_OF_FOLDS] [MAX_PER_CLASS] [SEED] [MAX_PROCESSES]
[FOLD]
Console script for a complete pimkl pipeline, including preprocessing and
analysis. For more details consult the following console scripts, which
are here executed in this order. `pimkl-preprocess --help` `pimkl-analyse
run-performance-analysis --help`
Options:
-fd, --data_csv_file PATH [required]
-nd, --data_name TEXT [required]
--model_name [EasyMKL|UMKLKNN|AverageMKL]
--help Show this message and exit.- C++14 capable C++ compiler
- cmake (>3.0.2)
- Python
Install the dependencies
pip install -r requirements.txtInstall the package
pip install .You can find a brief tutorial in the dedicated folder.
The PIMKL web-service has been deprecated in favour of the python package hosted in this repository. Please check the examples and the tutorials to use PIMKL in your research.
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.