- recipe bioconductor-proda
Differential Abundance Analysis of Label-Free Mass Spectrometry Data
- Homepage:
- License:
GPL-3
- Recipe:
Account for missing values in label-free mass spectrometry data without imputation. The package implements a probabilistic dropout model that ensures that the information from observed and missing values are properly combined. It adds empirical Bayesian priors to increase power to detect differentially abundant proteins.
- package bioconductor-proda¶
- versions:
1.16.0-0
,1.14.0-0
,1.12.0-0
,1.8.0-0
,1.6.0-0
,1.4.0-1
,1.4.0-0
,1.2.0-0
,1.0.0-0
- depends bioconductor-biocgenerics:
>=0.48.0,<0.49.0
- depends bioconductor-s4vectors:
>=0.40.0,<0.41.0
- depends bioconductor-summarizedexperiment:
>=1.32.0,<1.33.0
- depends r-base:
>=4.3,<4.4.0a0
- depends r-extradistr:
- 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 bioconductor-proda and update with:: mamba update bioconductor-proda
To create a new environment, run:
mamba create --name myenvname bioconductor-proda
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/bioconductor-proda:<tag> (see `bioconductor-proda/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/bioconductor-proda/README.html)