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svapls (version 1.0)

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

Description

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

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Version

Install

install.packages('svapls')

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Version

1.0

License

GPL-3

Maintainer

Sutirtha Chakraborty

Last Published

September 25th, 2012

Functions in svapls (1.0)

svpls

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

hfp

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

hidden_fac.dat

A gene expression data affected by a hidden variable.

fitModel

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

svapls-package

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

batch.dat

A gene expression data containing batch effects.