recipe deepsvr

DeepSVR stands for deep somatic variant refinement. It uses deep learning to classify real somatic and anomalous variants in paired tumor sequencing data.

Homepage:

https://github.com/griffithlab/deepsvr

License:

MIT

Recipe:

/deepsvr/meta.yaml

package deepsvr

versions:

0.1.0-0

depends bam-readcount:

depends click:

depends convert_zero_one_based:

depends h5py:

depends keras:

2.0.4

depends matplotlib:

depends numpy:

1.12.1

depends pandas:

0.20.3

depends python:

3.6.1

depends scikit-learn:

depends seaborn:

depends tensorflow:

<=1.0.1

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 deepsvr

and update with::

   mamba update deepsvr

To create a new environment, run:

mamba create --name myenvname deepsvr

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/deepsvr:<tag>

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

Download stats

Link to this page

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/deepsvr/README.html)