could not find function "rdirichlet"

[sby2019thu]

Hello! Thank you for developing such a fantastic software for deconvoluting the RNA-seq data.
However, I met an error when I ran the "run.prism" step:
> bp.res <- run.prism(prism = myPrism, n.cores=60)
Run Gibbs sampling...
Current time: 2025-05-19 14:42:27.921978
Estimated time to complete: 52mins
Estimated finishing time: 2025-05-19 15:33:31.601978
Start run...
Explicit sfStop() is missing: stop now.

Stopping cluster

snowfall 1.84-6.3 initialized (using snow 0.4-4): parallel execution on 60 CPUs.

Error in checkForRemoteErrors(val) :
60 nodes produced errors; first error: could not find function "rdirichlet"

Thank you for your kind reply.

[tinyi]

Hello. Thank you for your interest in using our tool.

Could you please let me know which R version you are using? Also could you do sessionInfo() after loading BayesPrism using "library(BayesPrism)" ?

Also, please make sure you are using library(BayesPrism) instead of require(BayesPrism) when loading the package. They might give different behaviors.

[sby2019thu]

Hello. My R version is 4.4.0.
Below is the sessioninfo after loading BayesPrism running "library(BayesPrism)".

> library(BayesPrism)
Loading required package: snowfall
Loading required package: snow
Loading required package: NMF
Loading required package: registry
Loading required package: rngtools
Loading required package: cluster
NMF - BioConductor layer [OK] | Shared memory capabilities [NO: synchronicity] | Cores 2/2
To enable shared memory capabilities, try: install.extras('
NMF
')
Warning messages:
1: replacing previous import ‘gplots::lowess’ by ‘stats::lowess’ when loading ‘BayesPrism’
2: replacing previous import ‘BiocParallel::register’ by ‘NMF::register’ when loading ‘BayesPrism’

> sessionInfo()
R version 4.4.0 (2024-04-24)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so; LAPACK version 3.9.0

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

time zone: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
[1] BayesPrism_2.2.2 NMF_0.28 bigmemory_4.6.4 Biobase_2.64.0 BiocGenerics_0.50.0 cluster_2.1.6 rngtools_1.5.2
[8] registry_0.5-1 snowfall_1.84-6.3 snow_0.4-4 cowplot_1.1.3 RColorBrewer_1.1-3 sceasy_0.0.7 reticulate_1.42.0
[15] SeuratWrappers_0.4.0 Seurat_5.3.0 SeuratObject_5.1.0 sp_2.2-0

loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.22 splines_4.4.0 later_1.4.2 bitops_1.0-9 tibble_3.2.1
[6] R.oo_1.26.0 polyclip_1.10-7 fastDummies_1.7.5 lifecycle_1.0.4 edgeR_4.2.1
[11] doParallel_1.0.17 globals_0.17.0 lattice_0.22-6 MASS_7.3-60.2 magrittr_2.0.3
[16] limma_3.60.4 plotly_4.10.4 remotes_2.5.0 metapod_1.12.0 httpuv_1.6.16
[21] sctransform_0.4.2 spam_2.11-1 spatstat.sparse_3.1-0 pbapply_1.7-2 abind_1.4-8
[26] zlibbioc_1.50.0 Rtsne_0.17 GenomicRanges_1.56.1 purrr_1.0.4 R.utils_2.12.3
[31] GenomeInfoDbData_1.2.12 IRanges_2.38.1 S4Vectors_0.42.1 ggrepel_0.9.6 irlba_2.3.5.1
[36] listenv_0.9.1 spatstat.utils_3.1-3 goftest_1.2-3 RSpectra_0.16-2 dqrng_0.4.1
[41] spatstat.random_3.3-1 fitdistrplus_1.2-2 parallelly_1.43.0 DelayedMatrixStats_1.26.0 codetools_0.2-20
[46] DelayedArray_0.30.1 scuttle_1.14.0 tidyselect_1.2.1 UCSC.utils_1.0.0 farver_2.1.2
[51] ScaledMatrix_1.12.0 matrixStats_1.5.0 stats4_4.4.0 spatstat.explore_3.3-2 jsonlite_2.0.0
[56] BiocNeighbors_1.22.0 progressr_0.15.1 ggridges_0.5.6 survival_3.5-8 iterators_1.0.14
[61] foreach_1.5.2 tools_4.4.0 ica_1.0-3 Rcpp_1.0.14 glue_1.8.0
[66] gridExtra_2.3 SparseArray_1.4.8 MatrixGenerics_1.16.0 GenomeInfoDb_1.40.1 dplyr_1.1.4
[71] BiocManager_1.30.25 fastmap_1.2.0 bluster_1.14.0 caTools_1.18.3 digest_0.6.37
[76] rsvd_1.0.5 R6_2.6.1 mime_0.13 colorspace_2.1-1 scattermore_1.2
[81] gtools_3.9.5 tensor_1.5 dichromat_2.0-0.1 spatstat.data_3.1-2 R.methodsS3_1.8.2
[86] tidyr_1.3.1 generics_0.1.3 data.table_1.17.0 httr_1.4.7 htmlwidgets_1.6.4
[91] S4Arrays_1.4.1 uwot_0.2.3 pkgconfig_2.0.3 gtable_0.3.6 lmtest_0.9-40
[96] SingleCellExperiment_1.26.0 XVector_0.44.0 htmltools_0.5.8.1 dotCall64_1.2 scales_1.4.0
[101] png_0.1-8 spatstat.univar_3.0-0 scran_1.32.0 bigmemory.sri_0.1.8 rstudioapi_0.16.0
[106] reshape2_1.4.4 uuid_1.2-1 nlme_3.1-164 zoo_1.8-14 stringr_1.5.1
[111] KernSmooth_2.23-22 parallel_4.4.0 miniUI_0.1.2 pillar_1.10.2 grid_4.4.0
[116] vctrs_0.6.5 RANN_2.6.2 gplots_3.2.0 promises_1.3.2 BiocSingular_1.20.0
[121] beachmat_2.20.0 xtable_1.8-4 locfit_1.5-9.10 cli_3.6.5 compiler_4.4.0
[126] rlang_1.1.6 crayon_1.5.3 future.apply_1.11.3 plyr_1.8.9 stringi_1.8.7
[131] viridisLite_0.4.2 deldir_2.0-4 gridBase_0.4-7 BiocParallel_1.38.0 lazyeval_0.2.2
[136] spatstat.geom_3.3-2 Matrix_1.6-5 RcppHNSW_0.6.0 patchwork_1.3.0 sparseMatrixStats_1.16.0
[141] future_1.34.0 ggplot2_3.5.2 statmod_1.5.0 shiny_1.9.1 SummarizedExperiment_1.34.0
[146] ROCR_1.0-11 igraph_2.1.4

[tinyi]

when using library(BayesPrism), does such error still persist?

[sby2019thu]

Yes, I persistently use "library(BayesPrism)" to load this package.

[tinyi]

We have received feedback from another user reporting the same issue. I suspect that this might be an OS-specific problem (Ubuntu perhaps) as I was not able to reproduce this error on our end (on a Rocky Linux 9.4 (Blue Onyx) OS). I will try creating a new fork and make some edits to the code and see if this can address the problem.

Will keep you posted on this. Thanks!

[tinyi]

Hello. I have tried adding rdirichlet to the environment. Could you please try re-installing the package and testing it again to see if it fixed the problem? Thank you very much.

[sby2019thu]

It successfully worked! Thank you very much for your attention and assistance!

[tinyi]

Thank you for your feedback. I will find a time to look into it, but if you run the run.prism with the default settings, you do not need to run update.theta since by default run.prism performs the update theta step.

…

On Sat, May 31, 2025 at 3:04 AM sby2019thu ***@***.***> wrote: *sby2019thu* left a comment (Danko-Lab/BayesPrism#119) <#119 (comment)> Sorry to bother you again. I ran "run.prism" successfully. But I met another problem when I ran "update.theta". bp.res.update <- update.theta(bp = bp.res) Update the reference matrix ... R Version: R version 4.4.0 (2024-04-24) snowfall 1.84-6.3 initialized (using snow 0.4-4): parallel execution on 60 CPUs. Stopping cluster Run Gibbs sampling using updated reference ... Current time: 2025-05-31 14:57:20.755467 Estimated time to complete: 28mins Estimated finishing time: 2025-05-31 15:24:56.115467 Start run... snowfall 1.84-6.3 initialized (using snow 0.4-4): parallel execution on 60 CPUs. Error in checkForRemoteErrors(val) : 60 nodes produced errors; first error: cannot open the connection — Reply to this email directly, view it on GitHub <#119 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AB4NHSZNQ7UDU22ZE42RK5T3BFIAFAVCNFSM6AAAAAB5M4STTGVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDSMRUGU2DONJQGU> . You are receiving this because you commented.Message ID: ***@***.***>