vsn: class.vsn – R documentation

Pricing

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

Get Started for Free

Documentation

vsn

class.vsn

Class to contain result of a vsn fit

Description

Class to contain result of a vsn fit

Creating Objects

new("vsn") vsn2(x) with x being an ExpressionSet.

Slots

coefficients:: A 3D array of size (number of strata) x (number of columns of the data matrix) x 2. It contains the fitted normalization parameters (see vignette).
strata:: A factor of length 0 or n. If its length is n, then its levels correspond to different normalization strata (see vignette).
mu:: A numeric vector of length n with the fitted parameters \hat{μ}_k, for k=1,...,n.
sigsq:: A numeric scalar, \hat{σ}^2.
hx:: A numeric matrix with 0 or n rows. If the number of rows is n, then hx contains the transformed data matrix.
lbfgsb:: An integer scalar containing the return code from the L-BFGS-B optimizer.
hoffset:: Numeric scalar, the overall offset c- see manual page of vsn2.
calib:: Character of length 1, see manual page of vsn2.

Methods

[: Subset
dim: Get dimensions of data matrix.
nrow: Get number of rows of data matrix.
ncol: Get number of columns of data matrix.
show: Print a summary of the object
exprs: Accessor to slot hx.
coef, coefficients: Accessors to slot coefficients.

Author(s)

Wolfgang Huber

Examples

data("kidney")
  v = vsn2(kidney)
  show(v)
  dim(v)
  v[1:10, ]

vsn

Variance stabilization and calibration for microarray data

v3.58.0

Artistic-2.0

Authors

Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth

Initial release