recipe scvis_galaxy

scvis is a python package for dimension reduction of high-dimensional biological data, especially single-cell RNA-sequencing (scRNA-seq) data.

Homepage:

https://github.com/shahcompbio/scvis

License:

Creative Commons Attribution 4.0 International License

Recipe:

/scvis_galaxy/meta.yaml

package scvis_galaxy

versions:

0.1.1-0

depends matplotlib:

>=1.5.1

depends nomkl:

depends numpy:

>=1.11.1

depends pandas:

>=0.19.1

depends pip:

depends python:

depends pyyaml:

>=3.11

depends setuptools:

depends tensorflow:

>=1.13

depends wheel:

requirements:

additional platforms:

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 scvis_galaxy

and update with::

   mamba update scvis_galaxy

To create a new environment, run:

mamba create --name myenvname scvis_galaxy

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/scvis_galaxy:<tag>

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

Notes

conda-forge::tensorflow requires GLIBC >=2.16. It should be present on most, but not all systems. See https://github.com/conda-forge/tensorflow-feedstock/issues/67

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