minMLST is a machine-learning based methodology for identifying a minimal subset of genes that preserves high discrimination among bacterial strains. It combines well known machine-learning algorithms and approaches such as XGBoost, distance-based hierarchical clustering, and SHAP. minMLST quantifies the importance level of each gene in an MLST scheme and allows the user to investigate the trade-off between minimizing the number of genes in the scheme vs preserving a high resolution among strains.
See more information in GitHub.
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Release files for minmlst 0.3.1
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| minmlst-0.3.1.tar.gz | 12.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| minmlst-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 26.7 kB
Release files / minmlst-0.3.1.tar.gz
| Download URL | minmlst-0.3.1.tar.gz |
|---|---|
| Size | 12.8 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.3
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Release files / minmlst-0.3.1-py3-none-any.whl
| Download URL | minmlst-0.3.1-py3-none-any.whl |
|---|---|
| Size | 13.9 kB |
| Tags | Python 3 |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.1.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.3
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