Hello,

I am encountering a fully reproducible failure when running DESeq2 in parallel using MulticoreParam on macOS (ARM). The error appears to originate inside BiocParallel and occurs even on trivial bplapply() examples.

Below is a complete minimal example, the full traceback, and my sessionInfo().

Minimal reproducible example

library(DESeq2)
library(BiocParallel)
set.seed(1)
dds <- makeExampleDESeqDataSet(n=1000, m=6)
dds <- DESeq(dds, parallel=TRUE, BPPARAM=MulticoreParam(4))

Output:

estimating size factors
estimating dispersions
gene-wise dispersion estimates: 4 workers
mean-dispersion relationship
final dispersion estimates, fitting model and testing: 4 workers
Warning in parallel::mccollect(wait = FALSE, timeout = 1) :
  1 parallel job did not deliver a result
Error in h(simpleError(msg, call)) :
  error in evaluating the argument 'args' in selecting a method for function 'do.call': wrong args for environment subassignment

Independent BiocParallel failure (no DESeq2)

library(BiocParallel)
param <- MulticoreParam(workers = 4)
x <- 1:12
res <- bplapply(X = x, FUN = \(i) i^2, BPPARAM = param)

Produces:

Warning in parallel::mccollect(wait = TRUE) :
  3 parallel jobs did not deliver results
Error in h(simpleError(msg, call)) :
  error in evaluating the argument 'args' in selecting a method for function 'do.call': wrong args for environment subassignment

FULL TRACEBACK (VERBATIM)

Error in h(simpleError(msg, call)) :
error in evaluating the argument 'args' in selecting a method for function 'do.call': wrong args for environment subassignment
12.
.reducer_add(reducer, njob, value)
11.
.reducer_add(reducer, njob, value)
10.
.collect_result(manager, reducer, progress, BPPARAM)
9.
.bploop_impl(ITER = ITER, FUN = FUN, ARGS = ARGS, BPPARAM = BPPARAM,
BPOPTIONS = BPOPTIONS, BPREDO = BPREDO, reducer = reducer,
progress.length = length(redo_index))
8.
bploop.lapply(manager, BPPARAM = BPPARAM, BPOPTIONS = BPOPTIONS,
...)
7.
bploop(manager, BPPARAM = BPPARAM, BPOPTIONS = BPOPTIONS, ...)
6.
.bpinit(manager = manager, X = X, FUN = FUN, ARGS = ARGS, BPPARAM = BPPARAM,
BPOPTIONS = BPOPTIONS, BPREDO = BPREDO)
5.
bplapply(levels(idx), function(l) {
objectSub <- estimateDispersionsMAP(object[idx == l, ], dispPriorVar = dispPriorVar,
quiet = TRUE, modelMatrix = modelMatrix)
nbinomWaldTest(objectSub, betaPrior = FALSE, quiet = TRUE, ...
4.
bplapply(levels(idx), function(l) {
objectSub <- estimateDispersionsMAP(object[idx == l, ], dispPriorVar = dispPriorVar,
quiet = TRUE, modelMatrix = modelMatrix)
nbinomWaldTest(objectSub, betaPrior = FALSE, quiet = TRUE, ...
3.
do.call(rbind, bplapply(levels(idx), function(l) {
objectSub <- estimateDispersionsMAP(object[idx == l, ], dispPriorVar = dispPriorVar,
quiet = TRUE, modelMatrix = modelMatrix)
nbinomWaldTest(objectSub, betaPrior = FALSE, quiet = TRUE, ...
2.
DESeqParallel(object, test = test, fitType = fitType, betaPrior = betaPrior,
full = full, reduced = reduced, quiet = quiet, modelMatrix = modelMatrix,
useT = useT, minmu = minmu, BPPARAM = BPPARAM)
1.
DESeq(dds, parallel = TRUE, BPPARAM = MulticoreParam(4))

sessionInfo()

R version 4.5.2 (2025-10-31)
Platform: aarch64-apple-darwin20
Running under: macOS Tahoe 26.1

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib 
LAPACK: /Library/Frameworks/R.framework/Versions/4.5-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.12.1

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

time zone: Europe/Paris
tzcode source: internal

attached base packages:
[1] stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] BiocParallel_1.44.0         DESeq2_1.50.2              
 [3] SummarizedExperiment_1.40.0 Biobase_2.70.0             
 [5] MatrixGenerics_1.22.0       matrixStats_1.5.0          
 [7] GenomicRanges_1.62.0        Seqinfo_1.0.0              
 [9] IRanges_2.44.0              S4Vectors_0.48.0           
[11] BiocGenerics_0.56.0         generics_0.1.4             

loaded via a namespace (and not attached):
 [1] Matrix_1.7-4        gtable_0.3.6        BiocManager_1.30.27
 [4] dplyr_1.1.4         compiler_4.5.2      tidyselect_1.2.1   
 [7] Rcpp_1.1.0          parallel_4.5.2      scales_1.4.0       
[10] yaml_2.3.11         fastmap_1.2.0       lattice_0.22-7     
[13] ggplot2_4.0.1       R6_2.6.1            XVector_0.50.0     
[16] S4Arrays_1.10.0     knitr_1.50          tibble_3.3.0       
[19] DelayedArray_0.36.0 pillar_1.11.1       RColorBrewer_1.1-3 
[22] rlang_1.1.6         xfun_0.54           S7_0.2.1           
[25] SparseArray_1.10.2  cli_3.6.5           magrittr_2.0.4     
[28] locfit_1.5-9.12     digest_0.6.39       grid_4.5.2         
[31] rstudioapi_0.17.1   lifecycle_1.0.4     vctrs_0.6.5        
[34] evaluate_1.0.5      glue_1.8.0          farver_2.1.2       
[37] codetools_0.2-20    abind_1.4-8         rmarkdown_2.30     
[40] pkgconfig_2.0.3     tools_4.5.2         htmltools_0.5.8.1

Questions

1. Is this a known issue with MulticoreParam on macOS ARM?

Thank you for your help.