vsn-package |
vsn |
class:vsn |
Class to contain result of a vsn fit |
class:vsnInput |
Class to contain input data and parameters for vsn functions |
coef,vsn-method |
Class to contain result of a vsn fit |
coefficients,vsn-method |
Class to contain result of a vsn fit |
coerce,RGList,NChannelSet-method |
Fit the vsn model |
dim,vsn-method |
Class to contain result of a vsn fit |
dim,vsnInput-method |
Class to contain input data and parameters for vsn functions |
exprs,vsn-method |
Class to contain result of a vsn fit |
justvsn |
Wrapper functions for vsn |
kidney |
Intensity data for 1 cDNA slide with two adjacent tissue samples
from a nephrectomy (kidney) |
logLik,vsnInput-method |
Calculate the log likelihood and its gradient for
the vsn model |
logLik-methods |
Calculate the log likelihood and its gradient for
the vsn model |
lymphoma |
Intensity data for 8 cDNA slides with CLL and DLBL samples from
the Alizadeh et al. paper in Nature 2000 |
meanSdPlot |
Plot row standard deviations versus row means |
meanSdPlot,ExpressionSet-method |
Plot row standard deviations versus row means |
meanSdPlot,matrix-method |
Plot row standard deviations versus row means |
meanSdPlot,vsn-method |
Plot row standard deviations versus row means |
meanSdPlot-methods |
Plot row standard deviations versus row means |
ncol,vsn-method |
Class to contain result of a vsn fit |
ncol,vsnInput-method |
Class to contain input data and parameters for vsn functions |
normalize.AffyBatch.vsn |
Wrapper for vsn to be used as a normalization method with expresso |
nrow,vsn-method |
Class to contain result of a vsn fit |
nrow,vsnInput-method |
Class to contain input data and parameters for vsn functions |
plotVsnLogLik |
Calculate the log likelihood and its gradient for
the vsn model |
predict,vsn-method |
Apply the vsn transformation to data |
sagmbAssess |
Simulate data and assess vsn's parameter estimation |
sagmbSimulateData |
Simulate data and assess vsn's parameter estimation |
scalingFactorTransformation |
The transformation that is applied to the scaling parameter of
the vsn model |
show,vsn-method |
Class to contain result of a vsn fit |
show,vsnInput-method |
Class to contain input data and parameters for vsn functions |
vsn |
Variance stabilization and calibration for microarray data. |
vsn-class |
Class to contain result of a vsn fit |
vsn2 |
Fit the vsn model |
vsn2,AffyBatch-method |
Fit the vsn model |
vsn2,ExpressionSet-method |
Fit the vsn model |
vsn2,matrix-method |
Fit the vsn model |
vsn2,NChannelSet-method |
Fit the vsn model |
vsn2,numeric-method |
Fit the vsn model |
vsn2,RGList-method |
Fit the vsn model |
vsn2-methods |
Fit the vsn model |
vsnh |
A function that transforms a matrix of microarray intensities. |
vsnInput |
Class to contain input data and parameters for vsn functions |
vsnInput-class |
Class to contain input data and parameters for vsn functions |
vsnMatrix |
Fit the vsn model |
vsnPlotPar |
Plot trajectories of calibration and transformation parameters for
a vsn fit |
vsnrma |
Wrapper functions for vsn |
[,vsn-method |
Class to contain result of a vsn fit |
[,vsnInput-method |
Class to contain input data and parameters for vsn functions |