Metadata-Version: 2.1
Name: pyserrf
Version: 0.2.1
Summary: Add your description here
Requires-Python: >=3.12
Description-Content-Type: text/markdown
Requires-Dist: numpy>=2.2.0
Requires-Dist: pandas>=2.2.3
Requires-Dist: pytest>=8.3.4
Requires-Dist: scikit-learn>=1.6.0
Requires-Dist: tqdm>=4.67.1

# pySERRF
Python implementation of the Systematic Error Removal Using Random Forest (SERRF) algorithm.
SERRF is a qc-based sample normalization method designed for large-scale untargeted metabolomics data.
The method was developed by the Fan et al. in 2015 (see https://slfan2013.github.io/SERRF-online/).
This is simply an attempt to port its functionality from R to python.
The package structure is based on SKlearn's transformers, with fit and transform methods.

Documentation can be found at https://pyserrf.readthedocs.io


TODO: Implement cross-validation (almost done)
TODO: Verify if injection time is accounted for with current code 
TODO: Add documentation 
TODO: Add more tests 
TODO: Add CLI 
