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