Use of matrix functions to adjust data via linear model

This is a wrapper function that adjusts for multiple additional experimental variables while protecting the contrast(s) of interest.

Usage

adjustCovariateMatrix(
  counts,
  covariate_df,
  vars_to_protect,
  return_coefficients = FALSE
)

Arguments

counts

matrix of transformed counts (vst, log, inverse rank normalized, etc.). Should have sample IDs as rownames, feature ID as colnames

covariate_df

dataframe with all covariates, sample names should be rownames. should be in the same order as the input matrix

vars_to_protect

character vector of column names that should be protected. the coefficients calculated for these variables will not be subtracted from the returned values

return_coefficients

logcal. default=FALSE

Value

matrix of adjusted counts