Get contrasts of estimated parameters

Usage

CompareParameters(
  obj,
  design_factor,
  reference,
  experimental,
  param_name,
  param_function,
  condition = NULL,
  features = NULL,
  exactMatch = TRUE,
  repeatID = NULL,
  formula_mean = NULL,
  sd_grouping_factors = NULL,
  fit_params = NULL,
  overwrite = TRUE,
  parameter = "log_kdeg"
)

Arguments

obj: An EZbakRFit object, which is an EZbakRFractions object on which AverageAndRegularize() has been run.
design_factor: Name of factor from metadf whose parameter estimates at different factor values you would like to compare. If you specify this, you need to also specify reference and experimental.
reference: Name of reference condition factor level value. Difference will be calculated as experimental - reference.
experimental: Name of condition factor level value to compare to reference. Difference will be calculated as experimental - reference.
param_name: If you want to assess the significance of a single parameter, rather than the comparison of two parameters, specify that one parameter's name here.
param_function: NOT YET IMPLEMENTED. Will allow you to specify more complicated functions of parameters when hypotheses you need to test are combinations of parameters rather than individual parameters or simple differences in two parameters.
condition: Same as design_factor, will be deprecated in favor of the former in later release.
features: Character vector of the set of features you want to stratify reads by and estimate proportions of each RNA population. The default of "all" will use all feature columns in the obj's cB.
exactMatch: If TRUE, then features and populations have to exactly match those for a given fractions table for that table to be used. Means that you can't specify a subset of features or populations by default, since this is TRUE by default.
repeatID: If multiple averages tables exist with the same metadata, then this is the numerical index by which they are distinguished.
formula_mean: An R formula object specifying how the parameter of interest depends on the sample characteristics for the averages object you want to use.
sd_grouping_factors: Metadf columns should data was grouped by when estimating standard deviations across replicates for the averages object you want to use.
fit_params: Character vector of parameter names in the averages object you would like to use.
overwrite: If TRUE, then identical output will be overwritten if it exists.
parameter: Parameter to average across replicates of a given condition.