- recipe bifrost-httr
BIFROST HTTr Analysis Package - Bayesian inference for region of signal threshold
- Homepage:
- License:
GPL / GPL-3.0
- Recipe:
BIFROST HTTr Analysis Package provides Bayesian inference for region of signal threshold analysis. The package implements statistical methods for analyzing high-throughput data with a focus on threshold detection and signal analysis.
- package bifrost-httr¶
- versions:
0.3.1-0,0.3.0-0,0.2.1-1,0.2.1-0,0.2.0-0,0.1.0-0- depends click:
- depends cmdstanpy:
>=1.2.0,<2.0- depends multiqc:
1.28- depends numpy:
>=2.0.0,<3.0- depends pandas:
>=2.0.0,<3.0- depends plotly:
>=6.0.0,<7.0- depends python:
>=3.10- depends pyyaml:
>=6.0- depends scipy:
>=1.10.0,<2.0- 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 bifrost-httr and update with:: mamba update bifrost-httr
To create a new environment, run:
mamba create --name myenvname bifrost-httr
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/bifrost-httr:<tag> (see `bifrost-httr/tags`_ for valid values for ``<tag>``)
Download stats¶
Link to this page¶
Render an 
badge with the following MarkDown:
[](http://bioconda.github.io/recipes/bifrost-httr/README.html)
