recipe gseapy

Gene Set Enrichment Analysis in Python

Homepage:

https://github.com/zqfang/gseapy

License:

MIT / MIT

Recipe:

/gseapy/meta.yaml

package gseapy

(downloads) docker_gseapy

versions:
1.1.4-11.1.4-01.1.3-11.1.3-01.1.2-11.1.2-01.1.1-01.1.0-01.0.6-0

1.1.4-11.1.4-01.1.3-11.1.3-01.1.2-11.1.2-01.1.1-01.1.0-01.0.6-01.0.5-01.0.4-11.0.4-01.0.3-01.0.2-01.0.1-01.0.0-00.14.0-00.13.0-00.12.1-00.12.0-10.12.0-00.10.8-00.10.7-00.10.6-00.10.5-00.10.4-00.10.3-00.10.2-00.10.1-00.10.0-00.9.19-00.9.18-00.9.17-00.9.16-00.9.15-00.9.13-00.9.9-00.9.8-00.9.7-00.9.5-10.9.3-10.9.3-00.9.2-00.9.1-00.9.0-00.8.11-00.8.6-00.8.3-00.8.2-00.7.4-30.7.4-00.7.3-00.7.2-00.6.2-00.6.0-00.5.3-00.5.2a0-00.4.2-0

depends matplotlib-base:

>=1.4.3

depends numpy:

>=1.13.0

depends pandas:

>=0.16

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

depends requests:

depends scipy:

depends tomli:

>=1.2.1

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 gseapy

and update with::

   mamba update gseapy

To create a new environment, run:

mamba create --name myenvname gseapy

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/gseapy:<tag>

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

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