recipe schpl

Hierarchical progressive learning pipeline for single-cell RNA-sequencing datasets

Homepage:

https://github.com/lcmmichielsen/scHPL

License:

MIT

Recipe:

/schpl/meta.yaml

Links:

doi: 10.1038/s41467-021-23196-8

package schpl

versions:

1.0.5-0

depends anndata:

>=0.7.4

depends matplotlib-base:

>=3.3.1

depends numpy:

>=1.19.2

depends pandas:

>=1.1.2,<2

depends python:

>=3.6

depends python-newick:

>=1.0.0,<1.1.dev0

depends scikit-learn:

>=0.23.2

depends scipy:

>=1.5.2

depends seaborn:

>=0.11.1

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 schpl

and update with::

   mamba update schpl

To create a new environment, run:

mamba create --name myenvname schpl

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/schpl:<tag>

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

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