recipe scar

scAR (single-cell Ambient Remover) is a deep learning model for ambient signal removal in droplet-based single cell omicsis.

Homepage:

https://github.com/Novartis/scar

License:

MIT

Recipe:

/scar/meta.yaml

package scar

versions:

0.7.0-0,  0.6.1-0,  0.6.0-0,  0.5.5-0,  0.5.4-0,  0.5.2-0,  0.5.1-0,  0.5.0-0,  0.4.4-0, 

0.7.0-0,  0.6.1-0,  0.6.0-0,  0.5.5-0,  0.5.4-0,  0.5.2-0,  0.5.1-0,  0.5.0-0,  0.4.4-0,  0.4.3-0,  0.4.2-0,  0.4.1-0,  0.4.0-0,  0.3.5-0,  0.3.4-0,  0.3.2-0,  0.3.0-0,  0.2.3-0,  0.2.2-0

depends pyro-ppl:

>=1.8.0

depends python:

>=3.10

depends pytorch:

>=1.10.0

depends scanpy:

depends scikit-learn:

>=1.0.1

depends seaborn:

>=0.11.2

depends setuptools:

>=68.1.2

depends tensorboard:

>=2.2.1

depends torchvision:

>=0.9.0

depends tqdm:

>=4.62.3

requirements:

additional platforms:

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 scar

and update with::

   mamba update scar

To create a new environment, run:

mamba create --name myenvname scar

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/scar:<tag>

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

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