Installation problem in R

[Poocee]

Dear Lorenzo,

I am encountering an issue when trying to install the immunedeconv package on the new R version 4.5. The installation fails with the error message indicating that the dependency limSolve is not available.

It seems that limSolve is currently unavailable or not compatible with R 4.5, which prevents the successful installation of immunedeconv. I have attempted to install limSolve directly using install.packages('limSolve') but the issue persists.

Could you please advise if there is a workaround or if there are plans to update the dependencies to support R 4.5?

Thank you very much for your assistance.

Best regards,
Stefano

Brief description of the problem

ERROR: dependency ‘limSolve’ is not available for package ‘immunedeconv’
Perhaps try a variation of:
install.packages('limSolve')
* removing ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/library/immunedeconv’
Warning message:
In i.p(...) :
  installation of package ‘/var/folders/tz/q8ch61c50_s9kycshmr1tkkh0000gn/T//RtmppdQdbg/file3832a50b02c/immunedeconv_2.1.0.tar.gz’ had non-zero exit status

Versions

R version 4.5.0 (2025-04-11)
Platform: x86_64-apple-darwin20
Running under: macOS Sequoia 15.5

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-x86_64/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/Rome
tzcode source: internal

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

other attached packages:
[1] GO.db_3.21.0 AnnotationDbi_1.71.0 IRanges_2.43.0 S4Vectors_0.47.0 rrvgo_1.21.1
[6] lubridate_1.9.4 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.4
[11] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.2 tidyverse_2.0.0
[16] gprofiler2_0.2.3 Biobase_2.69.0 BiocGenerics_0.55.0 generics_0.1.4

loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.17.1 jsonlite_2.0.0 umap_0.2.10.0 magrittr_2.0.3
[6] farver_2.1.2 rmarkdown_2.29 fs_1.6.6 vctrs_0.6.5 memoise_2.0.1
[11] askpass_1.2.1 rstatix_0.7.2 htmltools_0.5.8.1 curl_6.2.3 broom_1.0.8
[16] Formula_1.2-5 htmlwidgets_1.6.4 plotly_4.10.4 zoo_1.8-14 cachem_1.1.0
[21] igraph_2.1.4 mime_0.13 lifecycle_1.0.4 pkgconfig_2.0.3 Matrix_1.7-3
[26] R6_2.6.1 fastmap_1.2.0 shiny_1.10.0 digest_0.6.37 colorspace_2.1-1
[31] ps_1.9.1 RSpectra_0.16-2 RSQLite_2.4.0 org.Hs.eg.db_3.21.0 ggpubr_0.6.0
[36] km.ci_0.5-6 timechange_0.3.0 httr_1.4.7 abind_1.4-8 compiler_4.5.0
[41] remotes_2.5.0 bit64_4.6.0-1 withr_3.0.2 backports_1.5.0 carData_3.0-5
[46] DBI_1.2.3 pak_0.9.0 R.utils_2.13.0 ggsignif_0.6.4 openssl_2.3.3
[51] tools_4.5.0 httpuv_1.6.16 R.oo_1.27.1 glue_1.8.0 callr_3.7.6
[56] GOSemSim_2.35.0 promises_1.3.3 grid_4.5.0 gridBase_0.4-7 gtable_0.3.6
[61] tzdb_0.5.0 KMsurv_0.1-6 R.methodsS3_1.8.2 survminer_0.5.0 data.table_1.17.4
[66] hms_1.1.3 xml2_1.3.8 car_3.1-3 XVector_0.49.0 ggrepel_0.9.6
[71] pillar_1.10.2 yulab.utils_0.2.0 limma_3.65.1 later_1.4.2 splines_4.5.0
[76] lattice_0.22-7 survival_3.8-3 bit_4.6.0 tidyselect_1.2.1 locfit_1.5-9.12
[81] tm_0.7-16 Biostrings_2.77.1 knitr_1.50 gridExtra_2.3 NLP_0.3-2
[86] edgeR_4.7.2 xfun_0.52 statmod_1.5.0 pheatmap_1.0.13 stringi_1.8.7
[91] UCSC.utils_1.5.0 lazyeval_0.2.2 yaml_2.3.10 evaluate_1.0.3 wordcloud_2.6
[96] cli_3.6.5 xtable_1.8-4 reticulate_1.42.0 processx_3.8.6 survMisc_0.5.6
[101] treemap_2.4-4 Rcpp_1.0.14 GenomeInfoDb_1.45.4 png_0.1-8 parallel_4.5.0
[106] blob_1.2.4 viridisLite_0.4.2 slam_0.1-55 scales_1.4.0 crayon_1.5.3
[111] rlang_1.1.6 KEGGREST_1.49.0

[guidohooiveld]

FWIW:
I just installed immunedeconv from GitHub without any issues in R-4.5.1 running on Windows 11 (thus not on a Mac).
Since some dependencies are installed from source, Rtools (link) has to be installed as well, at least on a Windows machine.

Note that limSolve v2.0.1 is available/used with R-4.5.1 (also see item 31 of sessionInfo()).

I installed from GitHub using this line of code:
BiocManager::install(c("omnideconv/immunedeconv"), force=TRUE)

Then, using the included example dataset:

> library(immunedeconv)
Loading required package: EPIC
                                                                       
> res <- deconvolute(immunedeconv::dataset_racle$expr_mat, "quantiseq")

>>> Running quantiseq

Running quanTIseq deconvolution module

Gene expression normalization and re-annotation (arrays: FALSE)

Removing 17 noisy genes

Removing 15 genes with high expression in tumors

Signature genes found in data set: 135/138 (97.83%)

Mixture deconvolution (method: lsei)

Deconvolution successful!
> res
# A tibble: 11 × 5
   cell_type                    LAU125   LAU355 LAU1255  LAU1314
   <chr>                         <dbl>    <dbl>   <dbl>    <dbl>
 1 B cell                       0.0232 4.31e- 1 0.0250  4.92e- 1
 2 Macrophage M1                0.0110 5.51e- 4 0.0279  2.02e- 3
 3 Macrophage M2                0      0        0.00219 1.30e- 2
 4 Monocyte                     0.177  0        0       0       
 5 Neutrophil                   0      0        0.186   0       
 6 NK cell                      0.0490 0        0       0       
 7 T cell CD4+ (non-regulatory) 0.0101 4.42e- 1 0       3.77e- 1
 8 T cell CD8+                  0      2.93e- 2 0.0925  5.26e- 2
 9 T cell regulatory (Tregs)    0.0234 9.64e- 2 0.0599  6.28e- 2
10 Myeloid dendritic cell       0      0        0       0       
11 uncharacterized cell         0.706  2.33e-16 0.606   1.15e-16
> 
> 
> BiocManager::version()
[1] ‘3.21’
> R.Version()$version.string
[1] "R version 4.5.1 (2025-06-13 ucrt)"
>
> sessionInfo()
R version 4.5.1 (2025-06-13 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 22631)

Matrix products: default
  LAPACK version 3.12.1

locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

time zone: Europe/Amsterdam
tzcode source: internal

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

other attached packages:
[1] immunedeconv_2.1.0 EPIC_1.1.7        

loaded via a namespace (and not attached):
  [1] DBI_1.2.3                   httr2_1.2.1                
  [3] readxl_1.4.5                biomaRt_2.64.0             
  [5] rlang_1.1.6                 magrittr_2.0.4             
  [7] matrixStats_1.5.0           compiler_4.5.1             
  [9] RSQLite_2.4.3               mgcv_1.9-3                 
 [11] png_0.1-8                   vctrs_0.6.5                
 [13] quadprog_1.5-8              sva_3.56.0                 
 [15] stringr_1.5.2               pkgconfig_2.0.3            
 [17] crayon_1.5.3                fastmap_1.2.0              
 [19] dbplyr_2.5.1                XVector_0.48.0             
 [21] utf8_1.2.6                  tzdb_0.5.0                 
 [23] UCSC.utils_1.4.0            preprocessCore_1.70.0      
 [25] purrr_1.1.0                 bit_4.6.0                  
 [27] cachem_1.1.0                ComICS_1.0.4               
 [29] GenomeInfoDb_1.44.2         jsonlite_2.0.0             
 [31] limSolve_2.0.1              progress_1.2.3             
 [33] blob_1.2.4                  DelayedArray_0.34.1        
 [35] BiocParallel_1.42.2         parallel_4.5.1             
 [37] data.tree_1.2.0             prettyunits_1.2.0          
 [39] R6_2.6.1                    stringi_1.8.7              
 [41] RColorBrewer_1.1-3          limma_3.64.3               
 [43] genefilter_1.90.0           testit_0.13                
 [45] GenomicRanges_1.60.0        cellranger_1.1.0           
 [47] mMCPcounter_1.1.0           quantiseqr_1.16.0          
 [49] SummarizedExperiment_1.38.1 readr_2.1.5                
 [51] IRanges_2.42.0              Matrix_1.7-4               
 [53] splines_4.5.1               tidyselect_1.2.1           
 [55] dichromat_2.0-0.1           abind_1.4-8                
 [57] codetools_0.2-20            curl_7.0.0                 
 [59] lattice_0.22-7              tibble_3.3.0               
 [61] Biobase_2.68.0              withr_3.0.2                
 [63] KEGGREST_1.48.1             S7_0.2.0                   
 [65] survival_3.8-3              BiocFileCache_2.16.2       
 [67] xml2_1.4.0                  lpSolve_5.6.23             
 [69] Biostrings_2.76.0           pillar_1.11.0              
 [71] filelock_1.0.3              MatrixGenerics_1.20.0      
 [73] stats4_4.5.1                generics_0.1.4             
 [75] S4Vectors_0.46.0            hms_1.1.3                  
 [77] ggplot2_4.0.0               scales_1.4.0               
 [79] xtable_1.8-4                glue_1.8.0                 
 [81] tools_4.5.1                 annotate_1.86.1            
 [83] locfit_1.5-9.12             XML_3.99-0.19              
 [85] grid_4.5.1                  tidyr_1.3.1                
 [87] AnnotationDbi_1.70.0        edgeR_4.6.3                
 [89] nlme_3.1-168                GenomeInfoDbData_1.2.14    
 [91] cli_3.6.5                   rappdirs_0.3.3             
 [93] S4Arrays_1.8.1              dplyr_1.1.4                
 [95] gtable_0.3.6                digest_0.6.37              
 [97] BiocGenerics_0.54.0         SparseArray_1.8.1          
 [99] farver_2.1.2                memoise_2.0.1              
[101] lifecycle_1.0.4             httr_1.4.7                 
[103] statmod_1.5.0               bit64_4.6.0-1              
[105] MASS_7.3-65                
>