compute_posterior.eSVD: Compute posterior according to Gamma-Poisson model for eSVD...

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

Compute posterior according to Gamma-Poisson model for eSVD object

Description

The posterior is computed based on whatever input_obj$latest_Fit is set to.

Usage

## S3 method for class 'eSVD'
compute_posterior(
  input_obj,
  alpha_max = 1000,
  bool_adjust_covariates = F,
  bool_covariates_as_library = T,
  bool_return_components = F,
  bool_stabilize_underdispersion = T,
  library_min = 0.1,
  nuisance_lower_quantile = 0.01,
  pseudocount = 0,
  ...
)

Arguments

input_obj	eSVD object outputed from opt_esvd.eSVD.
alpha_max	Maximum value of numerator when computing posterior, default is 1e3.
bool_adjust_covariates	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_covariates_as_library	Boolean to include the donor covariates effects in the adjusted library size, default is TRUE
bool_return_components	Boolean to return the numerator and denominator of the posterior terms as well (which will themselves by matrices that are cell-by-gene matrices), default is FALSE
bool_stabilize_underdispersion	Boolean to stabilize the over-dispersion parameter, specifically to rescale all the over-dispersions the global mean over-disperion is less than 1, default is TRUE
library_min	All covariate-adjusted library size smaller than this value are set to this value, default is 0.1.
nuisance_lower_quantile	All the nuisance values that are smaller than this quantile are set to this quantile, default is 0.01
pseudocount	The additional count that is added to the count matrix, default is 0.
...	Additional parameters.

Value

eSVD object with posterior_mean_mat and posterior_var_mat appended to the list in input_obj[[input_obj[["latest_Fit"]]]].

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