gof_model

This function is used to perform the likelihood ratio test on the models chosen based on the BIC values from best_model to check for model adequacy.

gof_model(lbic, cexpr, lib.size, formula = NULL, workers = NULL, seed = NULL)

Arguments

lbic	A list of genes together with filtered read counts based on the selected distribution from best_model. Output from best_model.
cexpr	A dataframe that contains the covariate values. The rows of the dataframe are the corresponding samples/cells from the counts matrix from filter_counts. The cells of the dataframe are the covariates to be included in the GLM.
lib.size	A numeric vector that contains the total number of counts per cell from the counts matrix from filter_counts.
formula	A regression formula to fit the covariates in the ZINB GLM.
workers	Number of workers to be used in parallel computation using future.apply, with argument multisession.
seed	Seed number to be used in parallel computation using future.apply, with argument multisession

Value

A list of genes with the p-values from performing the GOF tests.