recipe pyscenic

Python implementation of the SCENIC pipeline for transcription factor inference from single-cell transcriptomics experiments.

Homepage:

https://github.com/aertslab/pySCENIC

Documentation:

https://scenic.aertslab.org

License:

GPL3 / GPL-3.0-or-later

Recipe:

/pyscenic/meta.yaml

Links:

doi: 10.1038/nmeth.4463, doi: 10.1038/s41592-023-01938-4, biotools: scenic

package pyscenic

(downloads) docker_pyscenic

versions:

0.12.1-0

depends aiohttp:

depends arboreto:

depends attrs:

depends boltons:

depends cloudpickle:

depends ctxcore:

depends cytoolz:

depends dask-core:

>=2023.4.1

depends dill:

depends distributed:

>=2023.4.1,<2023.5.0

depends frozendict:

depends fsspec:

depends interlap:

depends llvmlite:

depends loompy:

depends networkx:

depends numba:

>=0.51.2

depends numexpr:

depends numpy:

1.23.5

depends pandas:

>=1.3.5

depends pyarrow:

depends python:

>=3.6

depends pyyaml:

depends requests:

depends scikit-learn:

depends scipy:

depends tqdm:

depends umap-learn:

requirements:

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 pyscenic

and update with::

   mamba update pyscenic

To create a new environment, run:

mamba create --name myenvname pyscenic

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/pyscenic:<tag>

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

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