Package: ClusterSignificance 1.33.0

Jason T Serviss

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

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.

Authors:Jason T. Serviss [aut, cre], Jesper R. Gadin [aut]

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ClusterSignificance.pdf |ClusterSignificance.html✨
ClusterSignificance/json (API)
NEWS

# Install 'ClusterSignificance' in R:
install.packages('ClusterSignificance', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jasonserviss/clustersignificance/issues

Datasets:
  • mlpMatrix - Simulated data used to demonstrate the Mlp method.
  • pcpMatrix - Simulated data used to demonstrate the Pcp method.

On BioConductor:ClusterSignificance-1.33.0(bioc 3.20)ClusterSignificance-1.32.0(bioc 3.19)

bioconductor-package

10 exports 0.91 score 5 dependencies 2 mentions

Last updated 2 months agofrom:03f7b4f48d

Exports:classifyconf.intgetDatainitializemlppcppermuteplotpvalueshow

Dependencies:pracmaprincurveRColorBrewerRcppscatterplot3d

ClusterSignificance Vignette

Jesper Robert Gådin and Jason T. Serviss

Rendered fromClusterSignificance-vignette.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2018-07-16
Started: 2016-04-06

Readme and manuals

Help Manual

Help pageTopics
The ClusterSignificance package provides tools to assess if clusters have a separation different from random or permuted data.ClusterSignificance-package ClusterSignificance
Classification of the one dimensional points in a Pcp or Mlp object..ClassifiedPoints ClassifiedPoints ClassifiedPoints-class classify classify,Mlp-method classify,Pcp-method getData,ClassifiedPoints-method initialize,ClassifiedPoints-method plot,ClassifiedPoints,missing-method show,ClassifiedPoints-method
Projection of points into one dimension..Mlp getData,Mlp-method initialize,Mlp-method Mlp mlp mlp,matrix-method Mlp-class plot,Mlp,missing-method show,Mlp-method
Simulated data used to demonstrate the Mlp method.mlpMatrix
Projection of points into one dimension..Pcp getData getData,Pcp-method initialize,Pcp-method Pcp pcp pcp,matrix-method Pcp-class plot,Pcp,missing-method show,Pcp-method
Simulated data used to demonstrate the Pcp method.pcpMatrix
Permutation test.PermutationResults c,PermutationResults-method conf.int conf.int,PermutationResults-method getData,PermutationResults-method initialize,PermutationResults-method PermutationResults-class permute permute,matrix-method plot,PermutationResults,missing-method pvalue pvalue,PermutationResults-method show,PermutationResults-method