bioconda / packages / bioconductor-clustersignificance 1.16.0

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data

Installers

Info: This package contains files in non-standard labels.

conda install

  • linux-64  v1.8.2
  • osx-64  v1.8.2
  • noarch  v1.16.0
To install this package with conda run one of the following:
conda install -c bioconda bioconductor-clustersignificance
conda install -c bioconda/label/gcc7 bioconductor-clustersignificance
conda install -c bioconda/label/cf201901 bioconductor-clustersignificance

Description

The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data. The term class clusters here refers to, clusters of points representing known classes in the data. This is particularly useful to determine if a subset of the variables, e.g. genes in a specific pathway, alone can separate samples into these established classes. ClusterSignificance accomplishes this by, projecting all points onto a one dimensional line. Cluster separations are then scored and the probability of the seen separation being due to chance is evaluated using a permutation method.

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