recipe bioconductor-hopach

Hierarchical Ordered Partitioning and Collapsing Hybrid (HOPACH)

Homepage

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

License

GPL (>= 2)

Recipe

/bioconductor-hopach/meta.yaml

Links

biotools: hopach, doi: 10.1038/nmeth.3252

The HOPACH clustering algorithm builds a hierarchical tree of clusters by recursively partitioning a data set, while ordering and possibly collapsing clusters at each level. The algorithm uses the Mean/Median Split Silhouette (MSS) criteria to identify the level of the tree with maximally homogeneous clusters. It also runs the tree down to produce a final ordered list of the elements. The non-parametric bootstrap allows one to estimate the probability that each element belongs to each cluster (fuzzy clustering).

package bioconductor-hopach

Versions

2.48.0-0, 2.46.0-0, 2.44.0-1, 2.42.0-0, 2.40.0-0, 2.38.0-0

Depends

• bioconductor-biobase >=2.48.0,<2.49.0

• bioconductor-biocgenerics >=0.34.0,<0.35.0

• libblas >=3.8.0,<4.0a0

• libgcc-ng >=7.3.0

• liblapack >=3.8.0,<3.9.0a0

• r-base >=4.0,<4.1.0a0

• r-cluster

Required By

• bioconductor-phenotest

• bioconductor-scclassify

Installation

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

conda install bioconductor-hopach

and update with:

conda update bioconductor-hopach

or use the docker container:

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

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

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-hopach/README.html)