recipe galaxy-ml

APIs for Galaxy machine learning tools

Homepage

https://github.com/goeckslab/Galaxy-ML

License

MIT

Recipe

/galaxy-ml/meta.yaml

package galaxy-ml

Versions

0.9.1-2,  0.9.1-1,  0.9.1-0,  0.9.0-0,  0.8.3-2,  0.8.3-1,  0.8.3-0,  0.8.2-5,  0.8.2-4, 

0.9.1-2,  0.9.1-1,  0.9.1-0,  0.9.0-0,  0.8.3-2,  0.8.3-1,  0.8.3-0,  0.8.2-5,  0.8.2-4,  0.8.2-3,  0.8.2-2,  0.8.2-1,  0.8.2-0,  0.8.1-0,  0.8.0-0,  0.7.12-0,  0.7.11-0,  0.7.10-1,  0.7.10-0,  0.7.9-0,  0.7.8-0,  0.7.7-1,  0.7.7-0,  0.7.5-0,  0.7.4.1-0

Depends

• asteval >=0.9.14

• graphviz >=2.40.1

• h5py >=3.1,<3.4

• htslib

• imbalanced-learn >=0.8.0,<0.9

• joblib >=0.13.2,<1.0

• libgcc-ng >=10.3.0

• libstdcxx-ng >=10.3.0

• matplotlib-base

• mlxtend >=0.17,<0.18

• numpy >=1.21.0,<1.22

• pandas >=1.0,<1.3

• plotly >=4.10.0,<5.0

• pydot >=1.4

• pyfaidx

• pytabix

• python >=3.7,<3.8.0a0

• python_abi 3.7.* *_cp37m

• scikit-learn >=0.24,<0.25

• scikit-optimize >=0.9,<1.0

• scipy >=1.3.1

• skrebate >=0.60,<0.70

• tabix

• tensorflow >=2.5,<2.6

• tensorflow-estimator >=2.5,<2.6

• xgboost >=1.3,<1.4

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install galaxy-ml

and update with:

conda update galaxy-ml

or use the docker container:

docker pull quay.io/biocontainers/galaxy-ml:<tag>

(see galaxy-ml/tags for valid values for <tag>)

Download stats

Link to this page

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/galaxy-ml/README.html)