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svapls (version 1.1)

Surrogate variable analysis using partial least squares in a gene expression study.

Description

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

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Version

Install

install.packages('svapls')

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Version

1.1

License

GPL-3

Maintainer

Sutirtha Chakraborty

Last Published

March 13th, 2013

Functions in svapls (1.1)

svpls

Function for identfying the optimal ANCOVA model and detecting the genes that are truly differentially expressed between the two types of samples.

svapls-package

Surrogate variable analysis using Partial Least Squares in a gene expression data

hidden_fac.dat

A gene expression data affected by a hidden variable.

hfp

Function to construct a heatmap of the hidden variation in the gene expression data.

fitModel

Function to fit an ANCOVA model to the log transformed gene expression data, with a certain specified number of surrogate variables.