recipe cdna_cupcake

cDNA_Cupcake is a miscellaneous collection of Python and R scripts used for analyzing sequencing data.

Homepage:

https://github.com/Magdoll/cDNA_Cupcake

License:

BSD / BSD-3-Clause-Clear

Recipe:

/cdna_cupcake/meta.yaml

package cdna_cupcake

(downloads) docker_cdna_cupcake

versions:
29.0.0-028.0.0-128.0.0-022.0.0-122.0.0-019.0.0-018.1.0-018.0.0-017.0.0-0

29.0.0-028.0.0-128.0.0-022.0.0-122.0.0-019.0.0-018.1.0-018.0.0-017.0.0-016.0.0-015.1.0-014.2.0-014.0.0-013.0.0-012.5-012.4.0-112.4.0-012.3.0-012.1.0-112.1.0-012.0.0-011.0.0-010.0.1-09.1.1-09.0.3-08.7.3-05.8-05.3-15.3-0

depends bcbio-gff:

depends biopython:

depends bx-python:

>=0.7.3

depends graphviz:

depends libgcc-ng:

>=12

depends numpy:

>=1.21.6,<2.0a0

depends pysam:

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

depends r-base:

depends samtools:

>=1.10

depends scikit-learn:

requirements:

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 cdna_cupcake

and update with::

   mamba update cdna_cupcake

To create a new environment, run:

mamba create --name myenvname cdna_cupcake

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/cdna_cupcake:<tag>

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

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