Class to contain result of a vsn fit

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 \(\hat{\mu}_k\), for \(k=1,...,n\).

sigsq:

A numeric scalar, \(\hat{\sigma}^2\).

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

Wolfgang Huber

See also

vsn2

Examples

  data("kidney")
  v = vsn2(kidney)
  show(v)
#> vsn object for 8704 features and 2 samples.
#> sigsq=0.005
#> hx: 8704 x 2 matrix.
  dim(v)
#> [1] 8704    2
  v[1:10, ]
#> vsn object for 10 features and 2 samples.
#> sigsq=0.005
#> hx: 10 x 2 matrix.