gPCA: Batch Effect Detection via Guided Principal Components Analysis
Version 1.0

This package implements guided principal components analysis for the detection of batch effects in high-throughput data.

Browse man pages Browse package API and functions Browse package files

AuthorSarah Reese
Date of publication2013-07-31 17:55:22
MaintainerSarah Reese <reesese@vcu.edu>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("gPCA")

Man pages

caseDat: Case study copy number variation data
CumulativeVarPlot: Plot of the Cumulative Variance due to the Principal...
gDist: Density/Distribution Plot for gPCA
gPCA.batchdetect: Guided Principal Components Analysis
gPCA-package: Batch Effect Detection via Guided Principal Components...
PCplot: Principal Component Plot

Functions

CumulativeVarPlot Man page Source code
PCplot Man page Source code
caseDat Man page
gDist Man page Source code
gPCA Man page
gPCA-package Man page
gPCA.batchdetect Man page Source code

Files

inst
inst/doc
inst/doc/gPCA.R
inst/doc/gPCA.pdf
inst/doc/gPCA.Rnw
NAMESPACE
data
data/datalist
data/caseDat.rda
R
R/gDist.R
R/gPCA.batchdetect.R
R/PCplot.R
R/CumulativeVarPlot.R
vignettes
vignettes/gPCArefs.bib
vignettes/my-plainnat.bst
vignettes/Sweave.sty
vignettes/gPCA.Rnw
MD5
DESCRIPTION
man
man/gPCA.batchdetect.Rd
man/gPCA-package.Rd
man/PCplot.Rd
man/caseDat.Rd
man/gDist.Rd
man/CumulativeVarPlot.Rd
gPCA documentation built on May 20, 2017, 5:48 a.m.