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

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

Compute posterior according to Gamma-Poisson model for matrices and sparse matrices.

Description

Compute posterior according to Gamma-Poisson model for matrices and sparse matrices.

Usage

## Default S3 method:
compute_posterior(
  input_obj,
  case_control_variable,
  covariates,
  esvd_res,
  library_size_variable,
  nuisance_vec,
  alpha_max = 1000,
  bool_adjust_covariates = F,
  bool_covariates_as_library = T,
  bool_library_includes_interept = T,
  bool_return_components = F,
  bool_stabilize_underdispersion = T,
  library_min = 0.1,
  nuisance_lower_quantile = 0.01,
  pseudocount = 0,
  ...
)

Arguments

input_obj	Dataset (either matrix or dgCMatrix) where the n rows represent cells and p columns represent genes. The rows and columns of the matrix should be named.
case_control_variable	A string of the column name of covariates which depicts the case-control status of each cell. Notably, this should be a binary variable where a 1 is hard-coded to describe case, and a 0 to describe control.
covariates	matrix object with n rows with the same rownames as dat where the columns represent the different covariates. Notably, this should contain only numerical columns (i.e., all categorical variables should have already been split into numerous indicator variables).
esvd_res	Output of opt_esvd.default, notably with elements x_mat, y_mat and z_mat
library_size_variable	A string of the variable name (which must be in covariates) of which variable denotes the sequenced (i.e., observed) library size.
nuisance_vec	Vector of non-negative numerics of length ncol(input_obj), such as the output of estimate_nuisance.default.
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_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_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.
pseudocount	The additional count that is added to the count matrix, default is 0.
...	Additional parameters.

Value

A list of elements posterior_mean_mat and posterior_var_mat

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