Package Recipe 'pycistopic'

recipe pycistopic

pycisTopic is a Python module to simultaneously identify cell states and cis-regulatory topics from single cell epigenomics data.

Homepage:: https://github.com/aertslab/pycistopic
License:: OTHER
Recipe:: /pycistopic/meta.yaml

package pycistopic¶

Versions:

2.0a-0

Depends:

on adjusttext
on bbknn
on bs4
on gensim
on harmonypy
on igraph
on leidenalg
on loomxpy
on lxml
on macs2
on matplotlib-base <3.7
on numpy >=1.20.3
on pandas >=1.5,<2
on polars >=0.18.3
on pyarrow >=8.0.0
on pybiomart
on pyranges <0.0.128
on pyscenic
on python >=3.9
on ray-default
on scanorama
on scanpy
on scatac-fragment-tools
on scikit-learn
on scrublet
on seaborn
on statsmodels
on tmtoolkit

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 pycistopic

to add into an existing workspace instead, run:

pixi add pycistopic

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 pycistopic

Alternatively, to install into a new environment, run:

conda create -n envname pycistopic

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/pycistopic:<tag>

(see pycistopic/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/pycistopic/README.html)