I analyse microbiome data using

library(phyloseq)
library(microbiome)
library(DirichletMultinomial)

and several other libraries. Fitting Dirichlet-Multinomial models to count data dmn {DirichletMultinomial} takes quite a long time. Can the computation be run on multiple cpu cores in R. I tried:

dat <- abundances(pseq)
count <- as.matrix(t(dat))
fit <- lapply(1:25, dmn, count = count, verbose=TRUE)

replacing with:

library(parallel)
numCores <- detectCores()
...
fit <- mclapply(1:25, dmn, count = count, verbose=TRUE, mc.cores = numCores)

but it returns errorWarning message: In mclapply(1:25, dmn, count = count, verbose = TRUE, mc.cores = numCores) : all scheduled cores encountered errors in user code

I am using

R version 4.0.2 (2020-06-22) -- "Taking Off Again"
Copyright (C) 2020 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin17.0 (64-bit)
> detectCores()
[1] 4

Can anyone help?

Best regards, Marcin