recipe dapcy

An sklearn implementation of discriminant analysis of principal components (DAPC) for population genetics.

Homepage:

https://gitlab.com/uhasselt-bioinfo/dapcy

License:

MIT / MIT

Recipe:

/dapcy/meta.yaml

package dapcy

versions:

1.0.1-0,  0.1.1-0

depends aiohttp:

depends bed-reader:

depends cyvcf2:

depends joblib:

depends matplotlib-base:

depends numpy:

depends pandas:

depends python:

>=3.6

depends requests:

depends scikit-learn:

depends scipy:

depends seaborn-base:

depends sgkit:

depends yarl:

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 dapcy

and update with::

   mamba update dapcy

To create a new environment, run:

mamba create --name myenvname dapcy

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/dapcy:<tag>

(see `dapcy/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/dapcy/README.html)