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
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Release files for pyserrf 0.2.2
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Source distribution (sdist)
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| pyserrf-0.2.2.tar.gz | 12.2 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyserrf-0.2.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.1 kB
Release files / pyserrf-0.2.2.tar.gz
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Release files / pyserrf-0.2.2-py3-none-any.whl
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| Tags | Python 3 |
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