ClusterSignificance: The ClusterSignificance package provides tools to assess if class clusters in dimensionality reduced data representations have a separation different from permuted data
Version 1.4.0

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.

AuthorJason T. Serviss and Jesper R. Gadin
Bioconductor views Classification Clustering PrincipalComponent StatisticalMethod
Date of publicationNone
MaintainerJason T Serviss <jason.serviss@ki.se>
LicenseGPL-3
Version1.4.0
Package repositoryView on Bioconductor
InstallationInstall the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("ClusterSignificance")

Getting started

Package overview
README.md
ClusterSignificance Vignette

Popular man pages

classify: Classification of the one dimensional points in a Pcp or Mlp...
ClusterSignificance-package: The ClusterSignificance package provides tools to assess if...
mlp: Projection of points into one dimension.
mlpMatrix: Simulated data used to demonstrate the Mlp method.
pcp: Projection of points into one dimension.
pcpMatrix: Simulated data used to demonstrate the Pcp method.
permute: Permutation test
See all...

All man pages Function index File listing

Man pages

classify: Classification of the one dimensional points in a Pcp or Mlp...
ClusterSignificance-package: The ClusterSignificance package provides tools to assess if...
mlp: Projection of points into one dimension.
mlpMatrix: Simulated data used to demonstrate the Mlp method.
pcp: Projection of points into one dimension.
pcpMatrix: Simulated data used to demonstrate the Pcp method.
permute: Permutation test

Functions

.ClassifiedPoints Man page
.Mlp Man page
.Pcp Man page
.PermutationResults Man page
AUC Source code
AUC.calc Source code
ClassifiedPoints Man page
ClassifiedPoints-class Man page
ClusterSignificance Man page
ClusterSignificance-package Man page
Curve Source code
Mlp Man page
Mlp-class Man page
MlpPlotStep1 Source code
MlpPlotStep2 Source code
MlpPlotStep3 Source code
MlpPlotStep4 Source code
MlpPlotStep5 Source code
MlpPlotStep6 Source code
Pcp Man page
Pcp-class Man page
Pcp2DPlotStep1 Source code
Pcp2DPlotStep2 Source code
Pcp2DPlotStep3 Source code
Pcp2DPlotStep4 Source code
Pcp2DPlotStep5 Source code
Pcp2DPlotStep6 Source code
PermutationResults-class Man page
ROCdistance Source code
TpFpFnTn Source code
axisIntercept2D Source code
c,PermutationResults-method Man page
calculateCI Source code
calculateP Source code
classify Man page Man page
classify,Mlp-method Man page Man page
classify,Pcp-method Man page Man page
classifyWrapper Source code
codedMatrix Source code
combinedFunction Source code
conf.int Man page
conf.int,PermutationResults-method Man page
distMeanPointsToLineLineTo2D3D Source code
getData Man page
getData,ClassifiedPoints-method Man page
getData,Mlp-method Man page
getData,Pcp-method Man page
getData,PermutationResults-method Man page
groupAndDimensionMean Source code
initialize,ClassifiedPoints-method Man page
initialize,Mlp-method Man page
initialize,Pcp-method Man page
initialize,PermutationResults-method Man page
legend Source code
mlp Man page Man page
mlp,matrix-method Man page Man page
mlpMatrix Man page
movePointsSoMeanLineGoesThroughOrigo2D Source code
newScores Source code
normalizeMatrix Source code Source code
nputChecks Source code
pcp Man page Man page
pcp,matrix-method Man page Man page
pcpMatrix Man page
permMatrix Source code
permute Man page Man page
permute,matrix-method Man page Man page
plot,ClassifiedPoints,missing-method Man page
plot,Mlp,missing-method Man page
plot,Pcp,missing-method Man page
plot,PermutationResults,missing-method Man page
plotPcp2D Source code
plots Source code
projectMultidimensionalPointsOnMultidimensionalLine Source code
pvalue Man page
pvalue,PermutationResults-method Man page
reduceMultDimToOneDimAlongTheLine Source code
regressionVectorFromGroupMeans Source code
scorePermats Source code
scoreReal Source code
sensitivity Source code
setColors Source code
show,ClassifiedPoints-method Man page
show,Mlp-method Man page
show,Pcp-method Man page
show,PermutationResults-method Man page
showClassifiedPoints Source code
showMlp Source code
showPcp Source code
showPermutationResults Source code
specificity Source code
step1 Source code
step2 Source code
step3 Source code
step4 Source code
step5 Source code
step6 Source code
upperTriangle Source code
user.permutationsCheck Source code
vectorMatrixOrthogonalToMeanPointLine2D Source code

Files

.travis.yml
DESCRIPTION
NAMESPACE
NEWS
R
R/All-classes.R
R/ClusterSignificance-package.R
R/classifier-methods.R
R/initialize-methods.R
R/mlpMatrix.R
R/pcpMatrix.R
R/permutation-methods.R
R/plot-methods.R
R/projection-methods.R
R/show-methods.R
README.md
build
build/vignette.rds
data
data/mlpMatrix.rda
data/pcpMatrix.rda
inst
inst/data-raw
inst/data-raw/demoData.R
inst/doc
inst/doc/ClusterSignificance-vignette.R
inst/doc/ClusterSignificance-vignette.Rmd
inst/doc/ClusterSignificance-vignette.html
man
man/ClusterSignificance-package.Rd
man/classify.Rd
man/mlp.Rd
man/mlpMatrix.Rd
man/pcp.Rd
man/pcpMatrix.Rd
man/permute.Rd
tests
tests/testthat
tests/testthat.R
tests/testthat/test_classifier-methods.R
tests/testthat/test_permutation-methods.R
tests/testthat/test_plot-methods.R
tests/testthat/test_projection-methods.R
vignettes
vignettes/ClusterSignificance-vignette.Rmd
ClusterSignificance documentation built on May 20, 2017, 10:03 p.m.

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