Description Usage Arguments Details Value Author(s) Examples
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
.
1 2 3 4 5 6 7 8 9 | RUVNaiveRidge(Y, center = TRUE, nc_index, nu, kW, check.input = FALSE)
## Default S3 method:
RUVNaiveRidge(Y, center = TRUE, nc_index, nu, kW,
check.input = FALSE)
## S3 method for class 'simulateGEdata'
RUVNaiveRidge(Y, center = TRUE, nc_index, nu, kW,
check.input = FALSE)
|
Y |
A matrix of gene expression values or an object of class |
center |
A logical scalar; if |
nc_index |
A vector of indices of negative controls. |
nu |
A numeric scalar value of |
kW |
An integer setting the number of dimensions for the estimated noise. |
check.input |
A logical scalar; if |
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.
RUVNaiveRidge
returns a matrix of the cleaned (RUV-treated) centered gene expression values.
Saskia Freytag
1 2 3 4 5 6 7 8 | Y<-simulateGEdata(500, 500, 10, 2, 5, g=NULL, Sigma.eps=0.1, 250, 100, check.input=FALSE)
Y
Y.hat<-RUVNaiveRidge(Y, center=TRUE, nc_index=251:500, 0, 10, check.input=TRUE)
cor(Y.hat[,1:5])
Y$Sigma[1:5,1:5]
Y.hat<-RUVNaiveRidge(Y, center=TRUE, nc_index=251:500, 1000, 10, check.input=TRUE)
cor(Y.hat[,1:5])
Y$Sigma[1:5,1:5]
|
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