recipe bioconductor-snm

Supervised Normalization of Microarrays

Homepage

https://bioconductor.org/packages/3.11/bioc/html/snm.html

License

LGPL

Recipe

/bioconductor-snm/meta.yaml

Links

biotools: snm

SNM is a modeling strategy especially designed for normalizing high-throughput genomic data. The underlying premise of our approach is that your data is a function of what we refer to as study-specific variables. These variables are either biological variables that represent the target of the statistical analysis, or adjustment variables that represent factors arising from the experimental or biological setting the data is drawn from. The SNM approach aims to simultaneously model all study-specific variables in order to more accurately characterize the biological or clinical variables of interest.

package bioconductor-snm

(downloads) docker_bioconductor-snm

Versions

1.36.0-0, 1.34.0-0, 1.32.0-1, 1.32.0-0, 1.30.0-0, 1.28.0-0, 1.26.0-0

Depends
Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-snm

and update with:

conda update bioconductor-snm

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-snm:<tag>

(see bioconductor-snm/tags for valid values for <tag>)