recipe negative_training_sampler

Generates negative samples with the same GC distribution as the positive samples per chromosome.

Homepage:

https://github.com/kircherlab/negative_training_sampler

License:

MIT

Recipe:

/negative_training_sampler/meta.yaml

package negative_training_sampler

versions:

0.3.1-0,  0.3.0-0,  0.2.0-0,  0.1.0-0

depends bedtools:

depends click:

depends dask:

depends pandas:

depends pybedtools:

depends pysam:

>=0.15

depends python:

>=3.6

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 negative_training_sampler

and update with::

   mamba update negative_training_sampler

To create a new environment, run:

mamba create --name myenvname negative_training_sampler

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/negative_training_sampler:<tag>

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

Download stats

Link to this page

Render an badge with the following MarkDown:

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