- recipe basenji
Sequential regulatory activity predictions with deep convolutional neural networks.
- Homepage:
- License:
Apache / Apache-2.0
- Recipe:
- package basenji¶
- versions:
0.6-0,0.5.1-0,0.5-0,0.4.1647b01-0- depends astropy:
- depends cooler:
- depends cooltools:
- depends h5py:
- depends intervaltree:
- depends joblib:
- depends matplotlib-base:
- depends natsort:
- depends networkx:
- depends numpy:
- depends packaging:
- depends pandas:
- depends pillow:
- depends pybedtools:
- depends pybigwig:
- depends pysam:
- depends python:
>=3.8- depends scikit-learn:
- depends scipy:
- depends seaborn:
- depends statsmodels:
- depends tabulate:
- depends tensorflow:
- 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 basenji and update with:: mamba update basenji
To create a new environment, run:
mamba create --name myenvname basenji
with
myenvnamebeing 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/basenji:<tag> (see `basenji/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/basenji/README.html)
