recipe dram

Distilled and Refined Annotation of Metabolism: A tool for the annotation and curation of function for microbial and viral genomes

Homepage:

https://github.com/shafferm/DRAM/

Documentation:

https://github.com/shafferm/DRAM/wiki

License:

GPL / GPL-3.0

Recipe:

/dram/meta.yaml

Links:

doi: 10.1101/2020.06.29.177501

package dram

versions:

1.5.0-0,  1.4.6-2,  1.4.6-1,  1.4.6-0,  1.4.5-0,  1.4.3-0,  1.4.2-0,  1.4.1-0,  1.4.0-0, 

1.5.0-0,  1.4.6-2,  1.4.6-1,  1.4.6-0,  1.4.5-0,  1.4.3-0,  1.4.2-0,  1.4.1-0,  1.4.0-0,  1.3.5-0,  1.3.4-0,  1.3.3-0,  1.3.2-0,  1.3-0,  1.2.4-1,  1.2.4-0,  1.2.2-0,  1.2.1-0,  1.2.0-0,  1.1.1-0,  1.1.0-0,  1.0.6-0

depends altair:

>=4

depends barrnap:

depends curl:

depends hmmer:

depends mmseqs2:

>10.6d92c

depends networkx:

depends numpy:

depends openpyxl:

depends pandas:

>=1.5,<2

depends parallel:

depends prodigal:

depends python:

>=3.8

depends ruby:

depends scikit-bio:

>=0.5.8,<0.6

depends scipy:

>=1.9

depends sqlalchemy:

depends trnascan-se:

>=2

depends wget:

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 dram

and update with::

   mamba update dram

To create a new environment, run:

mamba create --name myenvname dram

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/dram:<tag>

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

Notes

Databases are required. Please run 'DRAM-setup.py prepare_databases' with the respective options.

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