Error in getClassDef(x@superClass, package = packageSlot(x))@virtual : no applicable method for `@` applied to an object of class "NULL"

[nfancy]

Hi,

Thanks for this package, I am getting this error with the MAST::zlm function. I am scratching my head and can't find a solution. Any pointer is hugely appreciated.

>   zlmCond <- MAST::zlm(
     formula = model_formula,
     sca = sca,
     exprs_value = 'logcounts',
     method = "glmer", # note: glmer requires a random effects var
     ebayes = F,
     parallel = F,
     fitArgsD = list(nAGQ = 0)
   )
Error in getClassDef(x@superClass, package = packageSlot(x))@virtual : 
  no applicable method for `@` applied to an object of class "NULL"
> traceback()
22: isVirtualExt(exti)
21: FUN(X[[i]], ...)
20: vapply(ext, F, NA, USE.NAMES = FALSE)
19: .selectSuperClasses(list(dsyMatrix = new("SClassExtension", subClass = structure("dpoMatrix", package = "Matrix"), 
        superClass = structure("dsyMatrix", package = "Matrix"), 
        package = "Matrix", coerce = function (from, strict = TRUE) 
        {
            class(from) <- "dsyMatrix"
            from
        }, test = function (object) 
        TRUE, replace = function (from, to, value) 
        {
            for (what in c("Dim", "Dimnames", "x", "uplo", "factors"
            )) slot(from, what) <- slot(value, what)
            from
        }, simple = TRUE, by = character(0), dataPart = FALSE, distance = 1), 
        unpackedMatrix = new("SClassExtension", subClass = structure("dpoMatrix", package = "Matrix"), 
            superClass = structure("unpackedMatrix", package = "Matrix"), 
            package = "Matrix", coerce = function (from, strict = TRUE) 
            {
                from <- {
                    class(from) <- "dsyMatrix"
                    from
     ...
18: diag(from, names = FALSE)
17: diag(from, names = FALSE)
16: asMethod(object)
15: as(rr, "corMatrix")
14: vcov.merMod(object@fitC)
13: vcov(object@fitC)
12: vcov(object@fitC)
11: .local(object, ...)
10: vcov(object, "C")
9: vcov(object, "C")
8: withCallingHandlers(expr, warning = function(w) {
       if (str_detect(conditionMessage(w), regexp)) 
           invokeRestart("muffleWarning")
   })
7: hushWarning(list(coefC = coef(object, which = "C"), vcovC = vcov(object, 
       "C"), deviance = rowm(deviance(object@fitC), deviance(object@fitD)), 
       df.null = rowm(nobs(object@fitC), nobs(object@fitD)), dispersion = rowm(sigma(object@fitC), 
           NA), coefD = coef(object, which = "D"), vcovD = vcov(object, 
           "D"), loglik = torowm(logLik(object)), converged = torowm(object@fitted)), 
       "nobs")
6: summarize(obj)
5: summarize(obj)
4: FUN(X[[i]], ...)
3: lapply(listEE, .fitGeneSet)
2: lapply(listEE, .fitGeneSet)
1: MAST::zlm(formula = model_formula, sca = sca, exprs_value = "logcounts", 
       method = fargs$mast_method, ebayes = fargs$ebayes, parallel = fargs$parallel, 
       fitArgsD = fit_args_D)

> sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.6 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

locale:
[1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C               LC_TIME=en_GB.UTF-8       
[4] LC_COLLATE=en_GB.UTF-8     LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
[7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

time zone: Europe/London
tzcode source: system (glibc)

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

other attached packages:
[1] data.table_1.14.8           MAST_1.27.1                 Matrix_1.6-5               
[4] SummarizedExperiment_1.32.0 SingleCellExperiment_1.24.0 IRanges_2.36.0             
[7] GenomicRanges_1.54.1        S4Vectors_0.40.1           

loaded via a namespace (and not attached):
 [1] R.methodsS3_1.8.2             progress_1.2.2                DirichletReg_0.7-1           
 [4] DT_0.30                       goftest_1.2-3                 Biostrings_2.70.1            
 [7] HDF5Array_1.30.0              vctrs_0.6.4                   spatstat.random_3.2-1        
[10] RApiSerialize_0.1.2           digest_0.6.33                 png_0.1-8                    
[13] ggrepel_0.9.4                 deldir_1.0-9                  parallelly_1.36.0            
[16] MASS_7.3-60                   reshape2_1.4.4                httpuv_1.6.12                
[19] foreach_1.5.2                 BiocGenerics_0.48.0           xfun_0.41                    
[22] ggfun_0.1.3                   ggpubr_0.6.0                  ellipsis_0.3.2               
[25] survival_3.5-7                doRNG_1.8.6                   memoise_2.0.1                
[28] ggbeeswarm_0.7.2              systemfonts_1.0.5             tidytree_0.4.5               
[31] zoo_1.8-12                    pbapply_1.7-2                 R.oo_1.25.0                  
[34] Formula_1.2-5                 prettyunits_1.2.0             rematch2_2.1.2               
[37] KEGGREST_1.42.0               promises_1.2.1                httr_1.4.7                   
[40] rstatix_0.7.2                 globals_0.16.2                fitdistrplus_1.1-11          
[43] rhdf5filters_1.14.0           stringfish_0.15.8             rhdf5_2.46.0                 
[46] rstudioapi_0.15.0             miniUI_0.1.1.1                generics_0.1.3               
[49] base64enc_0.1-3               babelgene_22.9                curl_5.1.0                   
[52] zlibbioc_1.48.0               ScaledMatrix_1.10.0           polyclip_1.10-6              
[55] GenomeInfoDbData_1.2.11       ExperimentHub_2.10.0          SparseArray_1.2.0            
[58] threejs_0.3.3                 interactiveDisplayBase_1.40.0 xtable_1.8-4                 
[61] stringr_1.5.0                 doParallel_1.0.17             evaluate_0.23                
[64] S4Arrays_1.2.0                BiocFileCache_2.10.1          preprocessCore_1.64.0        
[67] hms_1.1.3                     irlba_2.3.5.1                 qs_0.25.5                    
[70] colorspace_2.1-0              filelock_1.0.2                hdf5r_1.3.8                  
[73] apcluster_1.4.11              ROCR_1.0-11                   reticulate_1.34.0            
[76] spatstat.data_3.0-3           magrittr_2.0.3                lmtest_0.9-40                
[79] readr_2.1.4                   later_1.3.1                   viridis_0.6.4                
[82] ggtree_3.10.0                 lattice_0.22-5                spatstat.geom_3.2-7          
[85] future.apply_1.11.0           scattermore_1.2               XML_3.99-0.14                
[88] scuttle_1.12.0                cowplot_1.1.1                 matrixStats_1.1.0            
[91] RcppAnnoy_0.0.21              pillar_1.9.0                  nlme_3.1-163                 
[94] iterators_1.0.14              compiler_4.3.2                beachmat_2.18.0              
[97] stringi_1.7.12                minqa_1.2.6                   tensor_1.5                   
[100] plyr_1.8.9                    crayon_1.5.2                  abind_1.4-5                  
[103] scater_1.30.0                 ggdendro_0.1.23               gridGraphics_0.5-1           
[106] RNOmni_1.0.1.2                locfit_1.5-9.8                bib2df_1.1.2.0               
[109] sp_2.1-1                      terra_1.7-55                  bit_4.0.5                    
[112] UpSetR_1.4.0                  sandwich_3.0-2                dplyr_1.1.3                  
[115] whisker_0.4.1                 codetools_0.2-19              BiocSingular_1.18.0          
[118] crosstalk_1.2.0               monocle3_1.3.4                leaflet_2.2.0                
[121] paletteer_1.5.0               plotly_4.10.3                 mime_0.12                    
[124] splines_4.3.2                 Rcpp_1.0.11                   EWCE_1.10.2                  
[127] dbplyr_2.4.0                  sparseMatrixStats_1.14.0      maxLik_1.5-2                 
[130] knitr_1.45                    grr_0.9.5                     blob_1.2.4                   
[133] utf8_1.2.4                    BiocVersion_3.18.0            lme4_1.1-35.1                
[136] WriteXLS_6.4.0                fs_1.6.3                      listenv_0.9.0                
[139] DelayedMatrixStats_1.24.0     HGNChelper_0.8.1              english_1.2-6                
[142] orthogene_1.8.0               ggsignif_0.6.4                ggplotify_0.1.2              
[145] tibble_3.2.1                  statmod_1.5.0                 tzdb_0.4.0                   
[148] svglite_2.1.2                 pkgconfig_2.0.3               tools_4.3.2                  
[151] cachem_1.0.8                  RSQLite_2.3.2                 viridisLite_0.4.2            
[154] DBI_1.1.3                     rmarkdown_2.25                fastmap_1.1.1                
[157] scales_1.2.1                  grid_4.3.2                    ica_1.0-3                    
[160] gprofiler2_0.2.2              Seurat_4.4.0                  broom_1.0.5                  
[163] AnnotationHub_3.10.0          FNN_1.1.3.2                   patchwork_1.1.3              
[166] BiocManager_1.30.22           kBET_0.99.6                   dotCall64_1.1-0              
[169] carData_3.0-5                 RANN_2.6.1                    scFlow_0.7.2                 
[172] yaml_2.3.7                    MatrixGenerics_1.14.0         cli_3.6.1                    
[175] purrr_1.0.2                   stats4_4.3.2                  leiden_0.4.3                 
[178] lifecycle_1.0.4               uwot_0.1.16                   Biobase_2.62.0               
[181] homologene_1.4.68.19.3.27     backports_1.4.1               DropletUtils_1.22.0          
[184] BiocParallel_1.36.0           gtable_0.3.4                  rjson_0.2.21                 
[187] ggridges_0.5.4                progressr_0.14.0              parallel_4.3.2               
[190] ape_5.7-1                     limma_3.58.1                  jsonlite_1.8.7               
[193] edgeR_4.0.1                   miscTools_0.6-28              bitops_1.0-7                 
[196] ggplot2_3.4.4                 bit64_4.0.5                   assertthat_0.2.1             
[199] WebGestaltR_0.4.6             Rtsne_0.16                    yulab.utils_0.1.0            
[202] spatstat.utils_3.0-4          BiocNeighbors_1.20.0          SeuratObject_4.1.4           
[205] RcppParallel_5.1.7            riverplot_0.10                formattable_0.2.1            
[208] dqrng_0.3.1                   enrichR_3.2                   R.utils_2.12.2               
[211] lazyeval_0.2.2                shiny_1.7.5.1                 htmltools_0.5.7              
[214] sctransform_0.4.1             rappdirs_0.3.3                glue_1.6.2                   
[217] ewceData_1.10.0               rliger_1.0.0                  spam_2.10-0                  
[220] XVector_0.42.0                RCurl_1.98-1.12               treeio_1.26.0                
[223] mclust_6.0.0                  gridExtra_2.3                 boot_1.3-28.1                
[226] humaniformat_0.6.0            igraph_1.5.1                  R6_2.5.1                     
[229] tidyr_1.3.0                   forcats_1.0.0                 DoubletFinder_2.0.3          
[232] cluster_2.1.6                 rngtools_1.5.2                Rhdf5lib_1.24.0              
[235] aplot_0.2.2                   GenomeInfoDb_1.38.0           nloptr_2.0.3                 
[238] DelayedArray_0.28.0           tidyselect_1.2.0              vipor_0.4.5                  
[241] xml2_1.3.5                    car_3.1-2                     AnnotationDbi_1.64.0         
[244] future_1.33.0                 rsvd_1.0.5                    munsell_0.5.0                
[247] KernSmooth_2.23-22            htmlwidgets_1.6.2             RColorBrewer_1.1-3           
[250] biomaRt_2.58.0                rlang_1.1.2                   spatstat.sparse_3.0-3        
[253] spatstat.explore_3.2-5        fansi_1.0.5                   beeswarm_0.4.0        

The file was a little to big to attach here so I uploaded the reproducible data here.

https://www.dropbox.com/scl/fi/2zoiot4zx0ntyt4cg1ff0/mast_sca.zip?rlkey=xjkb7588ip38rq7khwnlge60u&dl=0

[amcdavid]

Hi,
Thanks the detailed report. What model are you fitting in model_formula?

[nfancy]

Apologies, for some reason, I didn't get a notification of your response. The model formula was ~cngenseon+(1|manifest) + diagnosis

[nfancy]

Here's a response I got from Matrix developer.

https://r-forge.r-project.org/tracker/?func=detail&atid=294&aid=6835&group_id=61

However, it did not solve the issue. Thanks.

[amcdavid]

@nfancy I think this is a binary compatibility issue that might be resolved by recompiling (and/or reinstalling?) some packages. Using the data you provided and a bioconductor 3.17 docker image with installed MAST I could run your model successfully. I'm sorry that I can't provide more guidance than "it works on my machine". The sessionInfo of this container is listed below -- It does have MAST 1.28.0 (which shouldn't matter), but otherwise the same versions of Matrix and lme4 as you reported above. I do see that you are on an ubuntu 18.xx versus ubuntu 20.xx in my container, which could cause some subtle issues with compiled code, I suppose.

Details

> sessionInfo() R version 4.3.1 (2023-06-16) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 22.04.3 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0

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

time zone: Etc/UTC
tzcode source: system (glibc)

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

other attached packages:
[1] MAST_1.28.0 SingleCellExperiment_1.24.0 SummarizedExperiment_1.32.0 Biobase_2.60.0
[5] GenomicRanges_1.54.1 GenomeInfoDb_1.38.5 IRanges_2.34.1 S4Vectors_0.38.2
[9] BiocGenerics_0.46.0 MatrixGenerics_1.12.3 matrixStats_1.1.0

loaded via a namespace (and not attached):
[1] utf8_1.2.3 generics_0.1.3 SparseArray_1.2.3 bitops_1.0-7 stringi_1.7.12
[6] lattice_0.21-8 hms_1.1.3 lme4_1.1-35.1 magrittr_2.0.3 grid_4.3.1
[11] plyr_1.8.9 Matrix_1.6-5 progress_1.2.3 purrr_1.0.2 fansi_1.0.4
[16] scales_1.3.0 abind_1.4-5 cli_3.6.1 rlang_1.1.1 crayon_1.5.2
[21] XVector_0.42.0 splines_4.3.1 munsell_0.5.0 DelayedArray_0.28.0 S4Arrays_1.2.0
[26] tools_4.3.1 reshape2_1.4.4 nloptr_2.0.3 minqa_1.2.6 dplyr_1.1.4
[31] colorspace_2.1-0 ggplot2_3.4.4 GenomeInfoDbData_1.2.11 boot_1.3-28.1 vctrs_0.6.4
[36] R6_2.5.1 lifecycle_1.0.3 zlibbioc_1.46.0 stringr_1.5.0 MASS_7.3-60
[41] pkgconfig_2.0.3 pillar_1.9.0 gtable_0.3.4 glue_1.6.2 data.table_1.14.8
[46] Rcpp_1.0.11 tibble_3.2.1 tidyselect_1.2.0 rstudioapi_0.15.0 nlme_3.1-163
[51] compiler_4.3.1 prettyunits_1.1.1 RCurl_1.98-1.13

[nfancy]

Hi, Thanks for checking. Can you think of any dependencies for MAST which depends on Matrix?

[amcdavid]

lme4 depends on matrix, and is being used in the example you provided. Did you reinstall lme4 from source? I sometimes find these issues require deleting packages manually from the R package library and reinstalling, which has its own pitfalls. Otherwise, you could work in one of the docker containers I linked to above (kind of annoying I realize).

[nfancy]

Thanks. We have incorporated MAST in our own package scFlow, hence it's mandatory that we sort this out. :(

[nfancy]

You are right, the culprit is lme4 since with method = "glm" it runs file. Unfortunately deleting and reinstalling lme4 with type = "source" did not help.

[amcdavid]

Oh nice! Since it's nextflow-based, I suppose you could just run the process that references MAST in a docker image, though that would probably constrain your users too much. What environments are you getting the failure? Just on local workstations, or in CI?

[nfancy]

We have both an R package with MAST-wrapper and nextflow-based pipeline, hence, we first need to find a fix within our system. The worst case scenario, we may need to wait until the next version release of lme4.