recipe learnmsa

learnMSA: Learning and Aligning large Protein Families

Homepage:

https://github.com/Gaius-Augustus/learnMSA

License:

MIT / MIT

Recipe:

/learnmsa/meta.yaml

Links:

doi: 10.1093/gigascience/giac104, biotools: learnMSA

package learnmsa

versions:

2.0.1-0,  1.3.4-0,  1.3.2-0,  1.3.1-0,  1.3.0-0,  1.2.4-0,  1.1.2-0,  1.1.1-0,  1.0.1-0

depends biopython:

>=1.69

depends imageio:

depends logomaker:

depends networkx:

depends pyfamsa:

depends python:

>=3.9

depends seaborn:

depends sentencepiece:

depends tensorflow:

>=2.7.0,<2.11

depends tensorflow-probability:

<=0.18.0

depends transformers:

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 learnmsa

and update with::

   mamba update learnmsa

To create a new environment, run:

mamba create --name myenvname learnmsa

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/learnmsa:<tag>

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

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