Extract parameter matrix for a new covariate data frame

This is the main function for extracting parameter matrices.

Usage

extractParaPop(
  sce,
  assay_use = "counts",
  marginal_list,
  n_cores = 2L,
  family_use,
  new_covariate,
  new_eqtl_geno_list,
  indiv_colname = "indiv",
  snp_colname = "snp_id",
  loc_colname = "POS",
  parallelization = c("pbmcapply", "future.apply", "parallel", "biocparallel"),
  BPPARAM = NULL,
  future.seed = FALSE,
  data_maxsize = 1,
  data,
  ...
)

Arguments

sce: a SingleCellExperiment object.
assay_use: a string scalar specifying the slot to use in input sce. The default is "counts".
marginal_list: a list of named features, each with the fitted object and other variables as output from fitMarginalPop.
n_cores: a positive integer value (greater or equal to 1) to specify the number of CPU cores used in parallelization. The default is 2.
family_use: a string scalar or vector of marginal distribution used.
new_covariate: a cell-by-covariate data frame obtained in the list output from constructDataPop. It must have a corr_group variable.
new_eqtl_geno_list: a list of eQTL genotype data frames for each gene to be simulated. If using same list as in fitMarginalPop, then the in those samples
indiv_colname: a string scalar of the sample ID variable in cell covariate of sce. The default is "indiv".
snp_colname: a string scalar for the SNP variable in eqtlgeno_df used in constructDataPop. The default is "snp_id".
loc_colname: a string scalar for the last column of eQTL annotation in eqtlgeno_df. The default is "POS".
parallelization: a string scalar specifying the parallelization backend used when extracting parameters. Must be one of "parallel", "future.apply", "biocparallel", or "pbmcapply". The default value is "parallel". See details.
BPPARAM: a BiocParallelParam class object (from BiocParallel R package) that must be specified when using parallelization = "biocparallel". Either BiocParallel::SnowParam() or BiocParallel::MulticoreParam() can be used to initialize, depending on the operating system. BPPARAM is not used in other parallelization options. The default is NULL.
future.seed: a logical or an integer (of length one or seven), or a list of length(X) with pre-generated random seeds that can be specified when using parallelization = "future.apply". See future.apply::future_eapply documentation for more details on its usage. future.seed is not used in other parallelization options. The default is FALSE.
data_maxsize: a positive numeric value used to set max marginal_list size in GiB increments. Used only when parallelization = "future.apply". The default is 1.
data: a cell-by-covariate data frame obtained in the list output from constructDataPop. It must have a corr_group variable. Used only in gamlss fits.
...: additional arguments passed to internal functions.

Value

a list of mean, sigma, and zero parameter cell by feature matrices:

mean_mat: a cell by feature matrix containing the conditional mean values.
sigma_mat: a cell by feature matrix containing the gene specific dispersion values.
zero_mat: a cell by feature matrix containing the gene specific zero probability values (for zip and zinb models).

Details

Parallelization options

If "parallel" is used then mcmapply is called from the parallel package; if "biocparallel" is used, then bpmapply is called from the BiocParallel package; if "future.apply" is used, then future_mapply is called from the future.apply package; if "pbmcapply" is used, then pbmcmapply is called from the pbmcapply package.

Examples

NULL
#> NULL