recipe bioconductor-topconfects

Top Confident Effect Sizes

Homepage:

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

License:

LGPL-2.1 | file LICENSE

Recipe:

/bioconductor-topconfects/meta.yaml

Rank results by confident effect sizes, while maintaining False Discovery Rate and False Coverage-statement Rate control. Topconfects is an alternative presentation of TREAT results with improved usability, eliminating p-values and instead providing confidence bounds. The main application is differential gene expression analysis, providing genes ranked in order of confident log2 fold change, but it can be applied to any collection of effect sizes with associated standard errors.

package bioconductor-topconfects

(downloads) docker_bioconductor-topconfects

versions:
1.18.0-01.16.0-01.14.0-01.10.0-01.8.0-01.6.0-11.6.0-01.4.0-01.2.0-0

1.18.0-01.16.0-01.14.0-01.10.0-01.8.0-01.6.0-11.6.0-01.4.0-01.2.0-01.0.0-1

depends r-assertthat:

depends r-base:

>=4.3,<4.4.0a0

depends r-ggplot2:

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-topconfects

and update with::

   mamba update bioconductor-topconfects

To create a new environment, run:

mamba create --name myenvname bioconductor-topconfects

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-topconfects:<tag>

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

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