Learn R Programming

KCsmart (version 2.30.0)

Multi sample aCGH analysis package using kernel convolution

Description

Multi sample aCGH analysis package using kernel convolution

Copy Link

Version

Version

2.30.0

License

GPL-3

Maintainer

Jorma de Ronde

Last Published

February 15th, 2017

Functions in KCsmart (2.30.0)

KcghDataSplit-class

Class "KcghDataSplit"
spmCollection-class

Sample point matrix collection
getSigRegionsCompKC

KCsmart Comparative calculate the signficant regions
KCData-class

Internal class "KCData"
compKcSigRegions-class

KC smart comparative
findSigLevelFdr

This function has not been properly implemented yet
KcghData-class

Class "KcghData"
plot

Plot a sample point matrix
sigSegments-class

Significant segments
hsSampleData

Homo Sapiens artificial cgh data set
compKc-class

KC smart comparative
KcghDataMirror-class

Class "KcghDataMirror"
calcSpm

KCsmart wrapper
write.table

Write summary of the significant regions to a table
KCsmart-package

KCsmart
compareSpmCollection

KCsmart Comparative calculate null distribution
plotScaleSpace

Plot multiple significant regions in one figure
mmMirrorLocs

Mirror locations of the mouse genome
hsMirrorLocs

Mirror locations of the human genome
calcSpmCollection

KCsmart Comparative wrapper
samplePointMatrix-class

Sample point matrix
KcghDataSum-class

Class "KcghDataSum"
idPoints

Identify points in sample point matrix plot
findSigLevelTrad

Find significance level
getSigSegments

Retrieve the significantly gained and lost regions including the corresponding, original probes
probeAnnotation-class

Class "probeAnnotation"