Package Recipe 'calour'

recipe calour

exploratory and interactive microbiome analyses based on heatmaps

Homepage:: https://biocore.github.io/calour/
Developer docs:: https://github.com/biocore/calour
License:: BSD / BSD-3-Clause
Recipe:: /calour/meta.yaml

Calour is a python package for processing, analysis and interactive exploration of microbiome (and other matrix form data), incorporating external databases.

package calour¶

Versions:

2020.8.6-0, 2019.5.1-0, 2018.10.1-0

Depends:

on biom-format
on docrep
on ipython
on ipywidgets
on matplotlib-base >=2.0
on numpy
on pandas
on pyqt >5
on python >=3.5
on scikit-bio >=0.5.1
on scikit-learn
on scipy
on statsmodels

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install calour

to add into an existing workspace instead, run:

pixi add calour

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install calour

Alternatively, to install into a new environment, run:

conda create -n envname calour

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

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

(see calour/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

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/calour/README.html)