gPCA: Batch Effect Detection via Guided Principal Components Analysis

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

AuthorSarah Reese
Date of publication2013-07-31 17:55:22
MaintainerSarah Reese <reesese@vcu.edu>
LicenseGPL (>= 2)
Version1.0

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Files

gPCA
gPCA/inst
gPCA/inst/doc
gPCA/inst/doc/gPCA.R
gPCA/inst/doc/gPCA.pdf
gPCA/inst/doc/gPCA.Rnw
gPCA/NAMESPACE
gPCA/data
gPCA/data/datalist
gPCA/data/caseDat.rda
gPCA/R
gPCA/R/gDist.R gPCA/R/gPCA.batchdetect.R gPCA/R/PCplot.R gPCA/R/CumulativeVarPlot.R
gPCA/vignettes
gPCA/vignettes/gPCArefs.bib
gPCA/vignettes/my-plainnat.bst
gPCA/vignettes/Sweave.sty
gPCA/vignettes/gPCA.Rnw
gPCA/MD5
gPCA/DESCRIPTION
gPCA/man
gPCA/man/gPCA.batchdetect.Rd gPCA/man/gPCA-package.Rd gPCA/man/PCplot.Rd gPCA/man/caseDat.Rd gPCA/man/gDist.Rd gPCA/man/CumulativeVarPlot.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.