recipe pyprophet

Python reimplementation of mProphet peak scoring

Homepage:

https://github.com/PyProphet/pyprophet

License:

BSD / BSD License

Recipe:

/pyprophet/meta.yaml

package pyprophet

(downloads) docker_pyprophet

versions:
2.2.5-42.2.5-32.2.5-12.2.5-02.2.4-02.2.3-02.1.12-02.1.11-02.1.10-2

2.2.5-42.2.5-32.2.5-12.2.5-02.2.4-02.2.3-02.1.12-02.1.11-02.1.10-22.1.10-12.1.10-02.1.6-02.1.5-12.1.5-02.1.4-02.1.3-00.24.1-10.24.1-00.22.0-0

depends click:

depends dataclasses:

depends hyperopt:

depends libgcc:

>=13

depends matplotlib-base:

depends numexpr:

>=2.1

depends numpy:

>=1.21,<3

depends numpy:

>=2.2.0,<3.0a0

depends pandas:

>=0.17

depends pypdf2:

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

depends scikit-learn:

>=0.17

depends scipy:

depends seaborn:

depends statsmodels:

>=0.8.0

depends tabulate:

depends typing-extensions:

depends xgboost:

requirements:

additional platforms:
linux-aarch64

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install pyprophet

and update with::

   mamba update pyprophet

To create a new environment, run:

mamba create --name myenvname pyprophet

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/pyprophet:<tag>

(see `pyprophet/tags`_ for valid values for ``<tag>``)

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