get_LD_UKB: dylib errors during tests

[bschilder]

In R console

Running this example seems to work totally fine on my Mac (albeit slowly and taking lots of memory, as usual):

query_dat <- echodata::BST1[seq(1, 50), ]
locus_dir <- file.path(tempdir(), echodata::locus_dir)
LD_list <- echoLD:::get_LD_UKB(
    query_dat = query_dat,
    locus_dir = locus_dir)

Using UK Biobank LD reference panel.
+ UKB LD file name: chr4_14000001_17000001
Downloading full .gz/.npz UKB files and saving to disk.
Downloading with axel [1thread(s)]: 
 https://data.broadinstitute.org/alkesgroup/UKBB_LD/chr4_14000001_17000001.gz ==> /var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/chr4_14000001_17000001.gz

axel download complete.
Time difference of 1.4 secs
Downloading with axel [1thread(s)]: 
 https://data.broadinstitute.org/alkesgroup/UKBB_LD/chr4_14000001_17000001.npz ==> /var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/chr4_14000001_17000001.npz

axel download complete.
Time difference of 22.9 secs
load_ld() python function input: /var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/chr4_14000001_17000001
Reading LD matrix into memory. This could take some time...
/var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/chr4_14000001_17000001.gz
/var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/chr4_14000001_17000001.npz
Processed URL: /var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/chr4_14000001_17000001
Some other message at the end
+ Full UKB LD matrix: 22,085 x 22,085
+ Full UKB LD SNP data.table: 22,085 x 5
50 x 50 LD_matrix (sparse)
Converting obj to sparseMatrix.
Saving sparse LD matrix ==> /var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpFq7D4S/results/GWAS/Nalls23andMe_2019/BST1/LD/BST1.UKB_LD.RDS
+ Removing .gz temp files.
+ Removing .npz temp files.

In tests during package checks

Nevertheless, when running unit tests during check, this error is produced. Not sure why testthat wouldn't have access to all the same libraries that the main R console does.

INTEL MKL ERROR: dlopen(/opt/anaconda3/lib/libmkl_intel_thread.1.dylib, 0x0009): Library not loaded: @rpath/libiomp5.dylib
  Referenced from: /opt/anaconda3/lib/libmkl_intel_thread.1.dylib
  Reason: tried: '/Library/Frameworks/R.framework/Resources/lib/libiomp5.dylib' (no such file), '/Library/Java/JavaVirtualMachines/jdk1.8.0_241.jdk/Contents/Home/jre/lib/server/libiomp5.dylib' (no such file).
Intel MKL FATAL ERROR: Cannot load libmkl_intel_thread.1.dylib.

Session info

R version 4.2.1 (2022-06-23)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.4

Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib

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

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

other attached packages:
[1] echoLD_0.99.6   snpStats_1.46.0 Matrix_1.4-1    survival_3.4-0 

loaded via a namespace (and not attached):
  [1] bitops_1.0-7                matrixStats_0.62.0          bit64_4.0.5                
  [4] filelock_1.0.2              progress_1.2.2              httr_1.4.4                 
  [7] rprojroot_2.0.3             GenomeInfoDb_1.32.3         tools_4.2.1                
 [10] utf8_1.2.2                  R6_2.5.1                    DT_0.24                    
 [13] DBI_1.1.3                   BiocGenerics_0.42.0         tidyselect_1.1.2           
 [16] prettyunits_1.1.1           bit_4.0.4                   curl_4.3.2                 
 [19] compiler_4.2.1              cli_3.3.0                   Biobase_2.56.0             
 [22] basilisk.utils_1.8.0        xml2_1.3.3                  DelayedArray_0.22.0        
 [25] rtracklayer_1.57.0          readr_2.1.2                 rappdirs_0.3.3             
 [28] stringr_1.4.1               digest_0.6.29               Rsamtools_2.12.0           
 [31] piggyback_0.1.4             R.utils_2.12.0              basilisk_1.8.1             
 [34] XVector_0.36.0              pkgconfig_2.0.3             htmltools_0.5.3            
 [37] echodata_0.99.11            MatrixGenerics_1.8.1        dbplyr_2.2.1               
 [40] fastmap_1.1.0               BSgenome_1.64.0             htmlwidgets_1.5.4          
 [43] rlang_1.0.4                 rstudioapi_0.14             RSQLite_2.2.16             
 [46] BiocIO_1.6.0                generics_0.1.3              jsonlite_1.8.0             
 [49] echoconda_0.99.6            BiocParallel_1.30.3         R.oo_1.25.0                
 [52] zip_2.2.0                   dplyr_1.0.9                 VariantAnnotation_1.42.1   
 [55] RCurl_1.98-1.8              magrittr_2.0.3              GenomeInfoDbData_1.2.8     
 [58] Rcpp_1.0.9                  S4Vectors_0.34.0            fansi_1.0.3                
 [61] reticulate_1.25             R.methodsS3_1.8.2           lifecycle_1.0.1            
 [64] stringi_1.7.8               yaml_2.3.5                  SummarizedExperiment_1.26.1
 [67] zlibbioc_1.42.0             BiocFileCache_2.4.0         grid_4.2.1                 
 [70] blob_1.2.3                  parallel_4.2.1              crayon_1.5.1               
 [73] dir.expiry_1.4.0            lattice_0.20-45             Biostrings_2.64.1          
 [76] splines_4.2.1               GenomicFeatures_1.48.3      hms_1.1.2                  
 [79] KEGGREST_1.36.3             pillar_1.8.1                GenomicRanges_1.48.0       
 [82] rjson_0.2.21                codetools_0.2-18            biomaRt_2.52.0             
 [85] stats4_4.2.1                pkgload_1.3.0               XML_3.99-0.10              
 [88] glue_1.6.2                  BiocManager_1.30.18         data.table_1.14.2          
 [91] tzdb_0.3.0                  png_0.1-7                   vctrs_0.4.1                
 [94] tidyr_1.2.0                 purrr_0.3.4                 assertthat_0.2.1           
 [97] cachem_1.0.6                openxlsx_4.2.5              echotabix_0.99.7           
[100] restfulr_0.0.15             downloadR_0.99.3            tibble_3.1.8               
[103] GenomicAlignments_1.32.1    AnnotationDbi_1.58.0        memoise_2.0.1              
[106] IRanges_2.30.1              ellipsis_0.3.2              here_1.0.1