ISANormalize {eisa} | R Documentation |
ISA works best if the input data is centered and
scaled. ISANormalize
performs this transformation.
ISANormalize (data, prenormalize = FALSE)
data |
An |
prenormalize |
If this argument is set to |
It was observed that the ISA works better if the input matrix is scaled and its rows have mean zero and standard deviation one.
An ISA step consists of two sub-steps, and this implies two different normalizations, in the first the rows (=features), in the second the columns (=samples) of the input matrix will be scaled and centered.
An ISAExpressionSet
object.
Gabor Csardi csardi.gabor@gmail.com
Bergmann S, Ihmels J, Barkai N: Iterative signature algorithm for the analysis of large-scale gene expression data Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Mar;67(3 Pt 1):031902. Epub 2003 Mar 11.
The ISA
function for an easier ISA workflow.
library(ALL) data(ALL) # Do the normalization ALL.normed <- ISANormalize(ALL) class(ALL.normed) dim(exprs(ALL.normed)) dim(featExprs(ALL.normed)) dim(sampExprs(ALL.normed)) # Check that we indeed have Z-scores all(abs(apply(featExprs(ALL.normed), 2, mean) ) < 1e-12) all(abs(1-apply(featExprs(ALL.normed), 2, sd)) < 1e-12) all(abs(apply(sampExprs(ALL.normed), 1, mean) ) < 1e-12) all(abs(1-apply(sampExprs(ALL.normed), 1, sd)) < 1e-12)