recipe scmidas

A torch-based integration method for single-cell multi-omic data.

Homepage:

https://github.com/labomics/midas

Documentation:

https://scmidas.readthedocs.io/en/latest

License:

MIT / MIT

Recipe:

/scmidas/meta.yaml

Links:

doi: 10.1038/s41587-023-02040-y

package scmidas

versions:

0.1.6-0,  0.1.5-0,  0.1.4-0,  0.1.3-0,  0.0.18-0,  0.0.17-0

depends anndata:

depends ipykernel:

depends lightning:

>=2.4.0

depends lightning-utilities:

>=0.11.8

depends matplotlib-base:

depends numpy:

depends pandas:

depends python:

>=3.9

depends pytorch:

>=2.5.1

depends requests:

depends scanpy:

depends scikit-learn:

depends scipy:

depends tensorboard:

depends toml:

depends torchaudio:

>=2.5.1

depends torchmetrics:

>=1.5.1

depends torchvision:

>=0.20.1

depends tornado:

depends tqdm:

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 scmidas

and update with::

   mamba update scmidas

To create a new environment, run:

mamba create --name myenvname scmidas

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/scmidas:<tag>

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

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