In a Bayesian framework, the parameters from Beta distribution, \(\alpha\) and \(\beta\), estimated from count data are used as pseudo-counts to estimate the posterior probabilities: $$p = (\alpha + success)/(\alpha + \beta + trials)$$.
betaBinPost(x, num.cores = 1L, tasks = 0L, verbose = TRUE, ...)A numerical vector, a matrix or a data.frame object.
Parameters for parallel computation using
BiocParallel-package: the number of cores to
use, i.e. at most how many child processes will be run simultaneously
(see bplapply and the number of tasks per job
(only for Linux OS).
if TRUE, prints the function log to stdout and a progress bar
Further arguments for betaDistEstimation function.