estimate_nuisance.eSVD: Estimate nuisance values for eSVD objects (i.e.,...

In linnykos/eSVD2: eSVD2 for performing the eSVD-DE for cohort-wide differential expression analysis

Estimate nuisance values for eSVD objects (i.e., over-dispersion)

Description

Assumes a Gamma-Poisson model where the mean and variance are proportionally related.

Usage

## S3 method for class 'eSVD'
estimate_nuisance(
  input_obj,
  bool_covariates_as_library = F,
  bool_library_includes_interept = T,
  bool_use_log = F,
  min_val = 1e-04,
  verbose = 0,
  ...
)

Arguments

input_obj	eSVD object outputed from opt_esvd.eSVD. Specifically, the nuisance parameters will be estimated based on the fit in input_obj[[input_obj[["latest_Fit"]]]].
bool_covariates_as_library	Boolean to adjust the numerator in the posterior by the donor covariates, default is FALSE. This parameter is experimental, and we have not yet encountered a scenario where it is useful to be set to be TRUE.
bool_library_includes_interept	Boolean if the intercept term from the eSVD matrix factorization should be included in the calculation for the covariate-adjusted library size, default is TRUE.
bool_use_log	Boolean if the nuisance (i.e., over-dispersion) parameter should be estimated on the log scale, default is FALSE.
min_val	Minimum value of the nuisance parameter.
verbose	Integer.
...	Additional parameters.

Value

eSVD object with nuisance_vec appended to the list in input_obj[[input_obj[["latest_Fit"]]]].

linnykos/eSVD2 documentation built on July 17, 2024, 12:01 a.m.