apply.scaling: Apply scaling factors
In iSubGen: Integrative Subtype Generation

Description Usage Arguments Details Value Author(s) Examples

Apply scaling factors prior to autoencoder

1	apply.scaling(data.matrices, scaling.factors);

`data.matrices`	list, where each element is a matrix. The list has one matrix for each data type to be scaled
`scaling.factors`	list with two elements named: \"center\" and \"scale\", and each element is a named numerical vector or a list of named numerical vectors. If scaling.factors$center or scaling.factors$scale are a list then each element needs to correspond to a one of the data matrices. Finally, the named numerical vectors should match the row and rownames from the corresponding data matrix.

The names for the data matrices and the center and scale lists all must match.

A list of matrices of the same format as the data.matrices

Natalie Fox

# Load molecular profiles for three data types and calculate scaling for each
example.molecular.data.dir <- paste0(path.package('iSubGen'),'/exdata/');
molecular.data <- list();
scaling.factors <- list();
for(i in c('cna','snv','methy')) {
  # Load molecular profiles from example files saved 
  # in the package as <data type>_profiles.txt
  molecular.data[[i]] <- load.molecular.aberration.data(
    paste0(example.molecular.data.dir,i,'_profiles.txt'),
    patients = c(paste0('EP00',1:9), paste0('EP0',10:30))
    );

  scaling.factors[[i]] <- list();

  scaling.factors[[i]]$center <- apply(molecular.data[[i]], 1, mean);
  scaling.factors[[i]]$scale <- apply(molecular.data[[i]], 1, sd);
  }

# Example 1: Transform the molecular profiles by the scaling factors
scaled.molecular.data <- apply.scaling(molecular.data, scaling.factors);

# Example 2: Transform one of the data types based on the scaling factors
scaled.molecular.data2 <- apply.scaling(
  molecular.data[[1]],
  scaling.factors[[1]]
  );