I went to estimate cell counts from a 450k RGSet with

    estimateCellCounts(RGSet, referencePlatform = c("IlluminaHumanMethylation450k"))

I got the following:

> cellCounts <- estimateCellCounts(RGSet, referencePlatform = c("IlluminaHumanMethylation450k")) 
[estimateCellCounts] Combining user data with reference (flow sorted) data. 'stringsAsFactors' is ignored
[estimateCellCounts] Processing user and reference data together.
[preprocessQuantile] Mapping to genome.
[preprocessQuantile] Fixing outliers.
[preprocessQuantile] Quantile normalizing. Error in normalize.quantiles(mat[Index2, ]) :   
 ERROR; return code from pthread_create() is 22

I tried to find this error but did not get anything that seemed helpful.

My sessionInfo:

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 19.04

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.5.so

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       

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

other attached packages:
 [1] IlluminaHumanMethylation450kanno.ilmn12.hg19_0.6.0 FlowSorted.Blood.450k_1.22.0                      
 [3] haven_2.1.1                                        gridExtra_2.3                                     
 [5] sva_3.32.1                                         genefilter_1.66.0                                 
 [7] mgcv_1.8-28                                        nlme_3.1-140                                      
 [9] lmtest_0.9-37                                      zoo_1.8-6                                         
[11] sandwich_2.5-1                                     MASS_7.3-51.1                                     
[13] data.table_1.12.2                                  R.utils_2.9.0                                     
[15] R.oo_1.22.0                                        R.methodsS3_1.7.1                                 
[17] foreign_0.8-71                                     IlluminaHumanMethylation450kmanifest_0.4.0        
[19] compare_0.2-6                                      minfi_1.30.0                                      
[21] bumphunter_1.26.0                                  locfit_1.5-9.1                                    
[23] iterators_1.0.10                                   foreach_1.4.4                                     
[25] Biostrings_2.52.0                                  XVector_0.24.0                                    
[27] SummarizedExperiment_1.14.0                        DelayedArray_0.10.0                               
[29] BiocParallel_1.18.0                                matrixStats_0.54.0                                
[31] Biobase_2.44.0                                     GenomicRanges_1.36.0                              
[33] GenomeInfoDb_1.20.0                                IRanges_2.18.1                                    
[35] S4Vectors_0.22.0                                   BiocGenerics_0.30.0                               
[37] forcats_0.4.0                                      stringr_1.4.0                                     
[39] dplyr_0.8.3                                        purrr_0.3.2                                       
[41] readr_1.3.1                                        tidyr_0.8.3                                       
[43] tibble_2.1.3                                       ggplot2_3.2.0                                     
[45] tidyverse_1.2.1                                    knitr_1.23    

After digging through the code, I found the error occurs when minfi calls normalize.quantiles.use.target from the preprocessCore library. There is an issue regarding the blas error on the preprocessCore github.

To work around it, this solution by the preprocessCore author worked for me (linux, ubuntu, conda setup). Basically, clone the current github, and install the library without threading:

git clone https://github.com/bmbolstad/preprocessCore.git
cd preprocessCore/
R CMD INSTALL --configure-args="--disable-threading"  .

I had the same error using oligo and affy, and the source of the error appears to be openblas >= 0.3.4. You can see in your R session history that you are using openblas 0.3.5.

For now, I'd replace openblas with blas until this problem is fixed upstream and the change is propagated to your OS distribution.

See https://support.bioconductor.org/p/117119/#123061