Package Recipe 'mpralib'

recipe mpralib

Library to analyze count data of MPRA experiments.

Homepage:: https://github.com/kircherlab/MPRAlib
License:: MIT
Recipe:: /mpralib/meta.yaml

package mpralib¶

Versions:

0.10.3-0, 0.10.2-0, 0.10.1-1, 0.10.1-0, 0.10.0-0, 0.9.1-0, 0.9.0-0, 0.8.2-0, 0.8.1-0,

0.10.3-0, 0.10.2-0, 0.10.1-1, 0.10.1-0, 0.10.0-0, 0.9.1-0, 0.9.0-0, 0.8.2-0, 0.8.1-0, 0.8.0-0, 0.7.4-0, 0.7.3-0, 0.7.2-0, 0.7.1-0, 0.7.0-0, 0.6.5-0, 0.6.4-0, 0.6.3-0, 0.6.2-0, 0.6.1-0, 0.6.0-0

Depends:

on anndata >=0.11.3
on click
on jsonschema
on matplotlib-base
on numpy
on pandas
on python >=3.10
on scikit-learn
on scipy
on seaborn
on tqdm

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 mpralib

to add into an existing workspace instead, run:

pixi add mpralib

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 mpralib

Alternatively, to install into a new environment, run:

conda create -n envname mpralib

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/mpralib:<tag>

(see mpralib/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/mpralib/README.html)