recipe bioconductor-pfamanalyzer

Identification of domain isotypes in pfam data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/pfamAnalyzeR.html

License:

MIT + file LICENSE

Recipe:

/bioconductor-pfamanalyzer/meta.yaml

Protein domains is one of the most import annoation of proteins we have with the Pfam database/tool being (by far) the most used tool. This R package enables the user to read the pfam prediction from both webserver and stand-alone runs into R. We have recently shown most human protein domains exist as multiple distinct variants termed domain isotypes. Different domain isotypes are used in a cell, tissue, and disease-specific manner. Accordingly, we find that domain isotypes, compared to each other, modulate, or abolish the functionality of a protein domain. This R package enables the identification and classification of such domain isotypes from Pfam data.

package bioconductor-pfamanalyzer

(downloads) docker_bioconductor-pfamanalyzer

versions:

1.6.0-0,  1.2.0-0,  1.0.1-0

depends r-base:

>=4.4,<4.5.0a0

depends r-dplyr:

depends r-magrittr:

depends r-readr:

depends r-stringr:

depends r-tibble:

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 bioconductor-pfamanalyzer

and update with::

   mamba update bioconductor-pfamanalyzer

To create a new environment, run:

mamba create --name myenvname bioconductor-pfamanalyzer

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-pfamanalyzer:<tag>

(see `bioconductor-pfamanalyzer/tags`_ for valid values for ``<tag>``)

Download stats

Link to this page

Render an install-with-bioconda 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-pfamanalyzer/README.html)