combine.integrative.features: Combine iSubGen integrative features

In iSubGen: Integrative Subtype Generation

Description

Combine a independent reduced features matrix (ex. from autoencoders) and pairwise integrative similarity matrices into one integrative feature matrix.

Usage

combine.integrative.features(irf.matrix, cis.matrix,
irf.rescale.recenter = NA, cis.rescale.recenter = NA, 
irf.rescale.denominator = NA, cis.rescale.denominator = NA,
irf.weights = rep(1, ncol(irf.matrix)), 
cis.weights = rep(1, ncol(cis.matrix)))

Arguments

irf.matrix	matrix of independent reduced features with patients as rows and features as columns
cis.matrix	matrix of consensus integrative similarity or integrative similarity features with patients as rows and features as columns
irf.rescale.recenter	either NA, "mean", a single number or a vector of numbers of length equal to the number of columns of irf
cis.rescale.recenter	either NA, "mean", a single number or a vector of numbers of length equal to the number of columns of cis
irf.rescale.denominator	either NA, "sd", a single number or a vector of numbers of length equal to the number of columns of irf
cis.rescale.denominator	either NA, "sd", a single number or a vector of numbers of length equal to the number of columns of cis
irf.weights	single number or vector of numbers of length equal to the number of columns of irf
cis.weights	single number or vector of numbers of length equal to the number of columns of cis

Details

The recenter values determine the how column centering is performed. If NA, no recentering is done. If the values equal "mean", then the mean of each column will be used. Otherwise, the numeric values specified will be used. The denominator values determine how column scaling is performed. If NA, no recentering is done. If the denominator values equal "sd", then the standard deviation of each column will be used. Otherwise, the numeric values specified will be used. The values used are returned by the function along with the compressed feature matrix to be recorded for reproducibility purposes.

Value

integrative.feature.matrix	a matrix of compressed features with patients as rows and features as columns
irf.rescale.recenter	a numeric vector with length equal to the number of columns of irf
cis.rescale.recenter	a numeric vector with length equal to the number of columns of cis
irf.rescale.denominator	a numeric vector with length equal to the number of columns of irf
cis.rescale.denominator	a numeric vector with length equal to the number of columns of cis
irf.weights	a numeric vector with length equal to the number of columns of irf
cis.weights	a numeric vector with length equal to the number of columns of cis

Author(s)

Natalie Fox

Examples

# Create matrices for combining
irf.matrix <- matrix(runif(25*4), ncol = 4);
rownames(irf.matrix) <- c(paste0('EP00',1:9), paste0('EP0',10:25));
cis.matrix <- matrix(runif(25*6), ncol=6);
rownames(cis.matrix) <- c(paste0('EP00',1:9), paste0('EP0',10:25));

# Example 1: Join the matrices without any weighting adjustments
isubgen.feature.matrix <- combine.integrative.features(
  irf.matrix,
  cis.matrix
  )$integrative.feature.matrix;

# Example 2: Combine matrices after scaling each column by subtracting the mean
# and dividing by the standard devation of the column
isubgen.feature.matrix.rescaled.result <- combine.integrative.features(
  irf.matrix,
  cis.matrix,
  irf.rescale.recenter = 'mean',
  cis.rescale.recenter = 'mean',
  irf.rescale.denominator = 'sd',
  cis.rescale.denominator = 'sd'
  );
isubgen.feature.matrix.2 <- isubgen.feature.matrix.rescaled.result$integrative.feature.matrix;

# Example 3: Combine matrices 
isubgen.feature.matrix.reweighted.result <- combine.integrative.features(
  irf.matrix,
  cis.matrix,
  irf.weights = 1/4,
  cis.weights = 1/6
  );
isubgen.feature.matrix.3 <- isubgen.feature.matrix.reweighted.result$integrative.feature.matrix;

iSubGen documentation built on April 22, 2021, 5:11 p.m.