svapls: Surrogate variable analysis using partial least squares in a gene expression study.
Version 1.4

Accurate identification of genes that are truly differentially expressed over two sample varieties, after adjusting for hidden subject-specific effects of residual heterogeneity.

AuthorSutirtha Chakraborty, Somnath Datta and Susmita Datta
Date of publication2013-09-20 08:13:19
MaintainerSutirtha Chakraborty <statistuta@gmail.com>
LicenseGPL-3
Version1.4
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("svapls")

Getting started

Package overview

Popular man pages

fitModel: Function to fit an ANCOVA model to the log transformed gene...
hfp: Function to construct a heatmap of the hidden variation in...
hidden_fac.dat: A gene expression data affected by a hidden variable.
svapls-package: Surrogate variable analysis using Partial Least Squares in a...
svpls: Function for identfying the optimal ANCOVA model and...
See all...

All man pages Function index File listing

Man pages

fitModel: Function to fit an ANCOVA model to the log transformed gene...
hfp: Function to construct a heatmap of the hidden variation in...
hidden_fac.dat: A gene expression data affected by a hidden variable.
svapls-package: Surrogate variable analysis using Partial Least Squares in a...
svpls: Function for identfying the optimal ANCOVA model and...

Functions

fitModel Man page Source code
hfp Man page Source code
hidden_fac.dat Man page
print.fitModel Source code
print.svpls Source code
summary.fitModel Source code
summary.svpls Source code
svapls Man page
svapls-package Man page
svpls Man page Source code

Files

NAMESPACE
data
data/hidden_fac.dat.rda
R
R/svpls.R
R/fitModel.R
R/hfp.R
MD5
DESCRIPTION
man
man/svapls-package.Rd
man/fitModel.Rd
man/svpls.Rd
man/hidden_fac.dat.Rd
man/hfp.Rd
svapls documentation built on May 19, 2017, 10:49 p.m.

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