RUVcorr (version 1.4.2)

RUVNaiveRidge: Removal of unwanted variation for gene correlations.

Description

RUVNaiveRidge applies the ridged version of global removal of unwanted variation to simulated or real gene expression data.

RUVNaiveRidge.default applies the ridged version of global removal of unwanted variation to matrices.

RUVNaiveRidge.simulateGEdata applies the ridged version of removal of unwanted variation to objects of class simulateGEdata.

Usage

RUVNaiveRidge(Y, center = TRUE, nc_index, nu, kW, check.input = FALSE)
"RUVNaiveRidge"(Y, center = TRUE, nc_index, nu, kW, check.input = FALSE)
"RUVNaiveRidge"(Y, center = TRUE, nc_index, nu, kW, check.input = FALSE)

Arguments

Y

A matrix of gene expression values or an object of class simulateGEdata.

center

A logical scalar; if TRUE the data is centered, if FALSE data is assumed to be already centered.

nc_index

A vector of indices of negative controls.

nu

A numeric scalar value of nu $\geq 0$.

kW

An integer setting the number of dimensions for the estimated noise.

check.input

A logical scalar; if TRUE all input is checked (not advisable for large simulations).

Value

RUVNaiveRidge returns a matrix of the cleaned (RUV-treated) centered gene expression values.

Details

The parameter kW controls how much noise is cleaned, whereas the parameter nu controls the amount of ridging to deal with possible dependence of the noise and the factor of interest.

References

Jacob L., Gagnon-Bartsch J., Speed T. Correcting gene expression data when neither the unwanted variation nor the factor of interest are observed. Berkley Technical Reports (2012).

Examples

Y<-simulateGEdata(500, 500, 10, 2, 5, g=NULL, Sigma.eps=0.1,
250, 100, intercept=TRUE, check.input=FALSE)
Y
Y.hat<-RUVNaiveRidge(Y, center=TRUE, nc_index=251:500, 0, 9, check.input=TRUE)
cor(Y.hat[,1:5])
Y$Sigma[1:5,1:5]
Y.hat<-RUVNaiveRidge(Y, center=FALSE, nc_index=251:500, 0, 10, check.input=TRUE)
cor(Y.hat[,1:5])
Y$Sigma[1:5,1:5]