recipe fanc

Framework for the ANalysis of C-data.

Homepage:

https://github.com/vaquerizaslab/fanc

Documentation:

https://vaquerizaslab.github.io/fanc

License:

ACADEMIC PUBLIC LICENSE (FAN-C)

Recipe:

/fanc/meta.yaml

package fanc

(downloads) docker_fanc

versions:

0.9.23b-20.9.0-10.9.0-0

depends biopython:

depends cooler:

>=0.8.0

depends future:

depends genomic_regions:

>=0.0.7

depends gridmap:

>=0.14.0

depends h5py:

depends intervaltree:

depends libgcc-ng:

>=10.3.0

depends matplotlib-base:

depends msgpack-numpy:

>=0.4.4.3

depends msgpack-python:

depends numpy:

>=1.16.0

depends pandas:

>=0.15.0

depends pillow:

depends progressbar2:

depends pybedtools:

depends pybigwig:

depends pysam:

>=0.9.1

depends pytables:

>=3.5.1

depends python:

>=3.7,<3.8.0a0

depends python_abi:

3.7.* *_cp37m

depends pyyaml:

>=5.1

depends scikit-image:

>=0.15.0

depends scikit-learn:

depends scipy:

depends seaborn:

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 fanc

and update with::

   mamba update fanc

To create a new environment, run:

mamba create --name myenvname fanc

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/fanc:<tag>

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

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