recipe bioconductor-emdomics

Earth Mover's Distance for Differential Analysis of Genomics Data

Homepage:

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

License:

MIT + file LICENSE

Recipe:

/bioconductor-emdomics/meta.yaml

The EMDomics algorithm is used to perform a supervised multi-class analysis to measure the magnitude and statistical significance of observed continuous genomics data between groups. Usually the data will be gene expression values from array-based or sequence-based experiments, but data from other types of experiments can also be analyzed (e.g. copy number variation). Traditional methods like Significance Analysis of Microarrays (SAM) and Linear Models for Microarray Data (LIMMA) use significance tests based on summary statistics (mean and standard deviation) of the distributions. This approach lacks power to identify expression differences between groups that show high levels of intra-group heterogeneity. The Earth Mover's Distance (EMD) algorithm instead computes the "work" needed to transform one distribution into another, thus providing a metric of the overall difference in shape between two distributions. Permutation of sample labels is used to generate q-values for the observed EMD scores. This package also incorporates the Komolgorov-Smirnov (K-S) test and the Cramer von Mises test (CVM), which are both common distribution comparison tests.

package bioconductor-emdomics

(downloads) docker_bioconductor-emdomics

versions:
2.32.0-0,  2.30.0-0,  2.28.0-0,  2.24.0-0,  2.22.0-0,  2.20.0-1,  2.20.0-0,  2.18.0-0,  2.16.0-0, 

2.32.0-0,  2.30.0-0,  2.28.0-0,  2.24.0-0,  2.22.0-0,  2.20.0-1,  2.20.0-0,  2.18.0-0,  2.16.0-0,  2.14.0-1,  2.14.0-0,  2.12.0-1,  2.12.0-0

depends bioconductor-biocparallel:

>=1.36.0,<1.37.0

depends bioconductor-preprocesscore:

>=1.64.0,<1.65.0

depends r-base:

>=4.3,<4.4.0a0

depends r-cdft:

depends r-emdist:

depends r-ggplot2:

depends r-matrixstats:

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-emdomics

and update with::

   mamba update bioconductor-emdomics

To create a new environment, run:

mamba create --name myenvname bioconductor-emdomics

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-emdomics:<tag>

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

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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