svapls (version 1.4)

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

1.4

License

GPL-3

Maintainer

Sutirtha Chakraborty

Last Published

September 20th, 2013

Functions in svapls (1.4)

svapls-package

Surrogate variable analysis using Partial Least Squares in a 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.

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.

svpls

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