recipe pyhalcyon

Halcyon: an accurate basecaller exploiting an encoder-decoder model with monotonic attention

Homepage:

https://pypi.org/project/pyhalcyon

Documentation:

https://github.com/relastle/halcyon

Developer docs:

https://github.com/relastle/halcyon

License:

GPLv3

Recipe:

/pyhalcyon/meta.yaml

package pyhalcyon

versions:

0.1.1-0

depends biopython:

>=1.75

depends click:

>=7.1.2

depends click-help-colors:

>=0.8

depends h5py:

>=2.10.0

depends logzero:

>=1.5.0

depends more-itertools:

>=8.4.0

depends numpy:

<1.17

depends python:

>=3.7

depends requests:

>=2.24.0

depends tensorflow:

<1.15.0

depends ujson:

>=1.35

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 pyhalcyon

and update with::

   mamba update pyhalcyon

To create a new environment, run:

mamba create --name myenvname pyhalcyon

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/pyhalcyon:<tag>

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

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