SummarizedExperiment::assay: on fastMNN object : object of type 'S4' is not subsettable

[nebetbastet]

Hello,

I have an issue with the 'fastMNN' function in batchelor.
I can't access the assay of the generated object as I get an error.

out= batchelor::fastMNN(objects.sce)
out

class: SingleCellExperiment
dim: 2000 10000
metadata(2): merge.info pca.info
assays(1): reconstructed
rownames(2000): PTGDS S100B ... BCAS1 AGPAT5
rowData names(1): rotation
colnames(10000): AGAGCGAGTTAGATGA-1 ATTGGTGCAATCTACG-1 ... TTAGGCATCATGGTCA-1
TGGCCAGCAATGGACG-1
colData names(1): batch
reducedDimNames(1): corrected
mainExpName: NULL
altExpNames(0):

assay(out)

Error in (function (cond) : erreur d'évaluation de l'argument 'x' lors de la sélection d'une méthode pour la fonction 'type' : object of type 'S4' is not subsettable

When I manually create an sce object, I don't encounter this problem.
Similarly, when I convert a Seurat object into an sce object, there are no issues accessing the assays.

Here's my SessionInfo()

R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=French_France.utf8 LC_CTYPE=French_France.utf8
[3] LC_MONETARY=French_France.utf8 LC_NUMERIC=C
[5] LC_TIME=French_France.utf8

time zone: Europe/Paris
tzcode source: internal

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

other attached packages:
[1] SeuratWrappers_0.3.1 genefilter_1.82.1 magick_2.8.0
[4] rgl_1.2.1 destiny_3.14.0 sinaplot_1.1.0
[7] plyr_1.8.8 RColorBrewer_1.1-3 ggplot2_3.4.3
[10] DESeq2_1.40.2 patchwork_1.1.3 UCell_2.4.0
[13] harmony_1.0.1 Rcpp_1.0.11 sscVis_0.1.0
[16] SingleCellExperiment_1.22.0 SummarizedExperiment_1.30.2 Biobase_2.60.0
[19] GenomicRanges_1.52.0 GenomeInfoDb_1.36.3 IRanges_2.34.1
[22] S4Vectors_0.38.2 BiocGenerics_0.46.0 MatrixGenerics_1.12.3
[25] matrixStats_1.0.0 dplyr_1.1.2 SeuratObject_4.1.3
[28] Seurat_4.3.0.1 markdown_1.8 knitr_1.44

loaded via a namespace (and not attached):
[1] spatstat.sparse_3.0-2 bitops_1.0-7 httr_1.4.7
[4] doParallel_1.0.17 dynamicTreeCut_1.63-1 tools_4.3.1
[7] sctransform_0.4.0 backports_1.4.1 ResidualMatrix_1.10.0
[10] utf8_1.2.3 R6_2.5.1 lazyeval_0.2.2
[13] uwot_0.1.16 GetoptLong_1.0.5 withr_2.5.0
[16] sp_2.0-0 gridExtra_2.3 progressr_0.14.0
[19] cli_3.6.1 spatstat.explore_3.2-3 sass_0.4.7
[22] mvtnorm_1.2-3 robustbase_0.99-0 spatstat.data_3.0-1
[25] proxy_0.4-27 ggridges_0.5.4 pbapply_1.7-2
[28] R.utils_2.12.2 parallelly_1.36.0 maps_3.4.1
[31] limma_3.56.2 TTR_0.24.3 RSQLite_2.3.1
[34] rstudioapi_0.15.0 impute_1.74.1 generics_0.1.3
[37] shape_1.4.6 ica_1.0-3 spatstat.random_3.1-6
[40] car_3.1-2 dendextend_1.17.1 Matrix_1.6-1.1
[43] ggbeeswarm_0.7.2 fansi_1.0.4 abind_1.4-5
[46] R.methodsS3_1.8.2 lifecycle_1.0.3 scatterplot3d_0.3-44
[49] yaml_2.3.7 carData_3.0-5 Rtsne_0.16
[52] blob_1.2.4 grid_4.3.1 promises_1.2.1
[55] crayon_1.5.2 miniUI_0.1.1.1 lattice_0.21-8
[58] beachmat_2.16.0 cowplot_1.1.1 annotate_1.78.0
[61] KEGGREST_1.40.0 pillar_1.9.0 ComplexHeatmap_2.16.0
[64] rjson_0.2.21 boot_1.3-28.1 future.apply_1.11.0
[67] codetools_0.2-19 leiden_0.4.3 glue_1.6.2
[70] remotes_2.4.2.1 pcaMethods_1.92.0 data.table_1.14.8
[73] vcd_1.4-11 vctrs_0.6.3 png_0.1-8
[76] spam_2.9-1 gtable_0.3.4 cachem_1.0.8
[79] ks_1.14.1 xfun_0.40 S4Arrays_1.0.6
[82] mime_0.12 RcppEigen_0.3.3.9.3 pracma_2.4.2
[85] survival_3.5-7 iterators_1.0.14 fields_15.2
[88] ellipsis_0.3.2 fitdistrplus_1.1-11 ROCR_1.0-11
[91] nlme_3.1-163 xts_0.13.1 bit64_4.0.5
[94] RcppAnnoy_0.0.21 bslib_0.5.1 irlba_2.3.5.1
[97] vipor_0.4.5 KernSmooth_2.23-22 DBI_1.1.3
[100] colorspace_2.1-0 nnet_7.3-19 smoother_1.1
[103] ggrastr_1.0.2 tidyselect_1.2.0 bit_4.0.5
[106] extrafontdb_1.0 curl_5.0.2 compiler_4.3.1
[109] BiocNeighbors_1.18.0 DelayedArray_0.26.7 plotly_4.10.2
[112] scales_1.2.1 hexbin_1.28.3 DEoptimR_1.1-2
[115] lmtest_0.9-40 stringr_1.5.0 digest_0.6.33
[118] goftest_1.2-3 spatstat.utils_3.0-3 rmarkdown_2.25
[121] XVector_0.40.0 RhpcBLASctl_0.23-42 base64enc_0.1-3
[124] htmltools_0.5.6 pkgconfig_2.0.3 extrafont_0.19
[127] sparseMatrixStats_1.12.2 fastmap_1.1.1 ggthemes_4.2.4
[130] rlang_1.1.1 GlobalOptions_0.1.2 htmlwidgets_1.6.2
[133] shiny_1.7.5 DelayedMatrixStats_1.22.6 jquerylib_0.1.4
[136] zoo_1.8-12 jsonlite_1.8.7 BiocParallel_1.34.2
[139] mclust_6.0.0 R.oo_1.25.0 BiocSingular_1.16.0
[142] RCurl_1.98-1.12 magrittr_2.0.3 scuttle_1.10.2
[145] GenomeInfoDbData_1.2.10 dotCall64_1.0-2 munsell_0.5.0
[148] viridis_0.6.4 reticulate_1.32.0 stringi_1.7.12
[151] zlibbioc_1.46.0 MASS_7.3-60 parallel_4.3.1
[154] listenv_0.9.0 ggrepel_0.9.3 deldir_1.0-9
[157] Biostrings_2.68.1 splines_4.3.1 tensor_1.5
[160] circlize_0.4.15 locfit_1.5-9.8 ranger_0.15.1
[163] igraph_1.5.1 ggpubr_0.6.0 spatstat.geom_3.2-5
[166] ggsignif_0.6.4 RcppHNSW_0.5.0 ScaledMatrix_1.8.1
[169] reshape2_1.4.4 XML_3.99-0.14 evaluate_0.21
[172] BiocManager_1.30.22 laeken_0.5.2 batchelor_1.16.0
[175] foreach_1.5.2 httpuv_1.6.11 Rttf2pt1_1.3.12
[178] VIM_6.2.2 RANN_2.6.1 tidyr_1.3.0
[181] purrr_1.0.2 polyclip_1.10-4 future_1.33.0
[184] clue_0.3-65 scattermore_1.2 gridBase_0.4-7
[187] rsvd_1.0.5 broom_1.0.5 xtable_1.8-4
[190] e1071_1.7-13 RSpectra_0.16-1 rstatix_0.7.2
[193] later_1.3.1 viridisLite_0.4.2 class_7.3-22
[196] tibble_3.2.1 moduleColor_1.8-4 memoise_2.0.1
[199] AnnotationDbi_1.62.2 beeswarm_0.4.0 cluster_2.1.4
[202] ggplot.multistats_1.0.0 globals_0.16.2

Thank you for your help

[LTLA]

Sorry for the late reply. I don't have any issues running the example:

library(batchelor)
example(fastMNN, echo=FALSE)
out
## class: SingleCellExperiment 
## dim: 200 100 
## metadata(2): merge.info pca.info
## assays(1): reconstructed
## rownames: NULL
## rowData names(1): rotation
## colnames: NULL
## colData names(1): batch
## reducedDimNames(1): corrected
## mainExpName: NULL
## altExpNames(0):

assay(out)
## <200 x 100> LowRankMatrix object of type "double":
##                [,1]         [,2]         [,3] ...       [,99]      [,100]
##   [1,] -0.041500974 -0.041187990 -0.065122142   . -0.01857182 -0.08582027
##   [2,]  0.019251114 -0.047421044 -0.020124255   . -0.04065221  0.01079485
##   [3,] -0.001653034  0.017117968 -0.038393065   . -0.07142613 -0.07357877
##   [4,] -0.044129094 -0.061465542 -0.093328064   . -0.02522488 -0.05275507
##   [5,] -0.028562310 -0.022114883 -0.047984941   . -0.12481886 -0.01802864
##    ...            .            .            .   .           .           .
## [196,] -0.034075842 -0.121444735 -0.007966894   . -0.04559586 -0.06874582
## [197,] -0.077225050  0.003219620 -0.070414809   .  0.03878306 -0.07472732
## [198,] -0.068255656 -0.021519339 -0.018424398   . -0.05250330 -0.09911245
## [199,] -0.034577621 -0.086351051 -0.045710427   . -0.08996022 -0.01574235
## [200,] -0.034046424 -0.049210218 -0.092373174   . -0.08422264 -0.13358312

It would be helpful to see str(assay(out, withDimnames=FALSE))

[moosa-r]

Dear @LTLA ,

I also encounter this error even when running the example provided in fastMNN function's Documentation.

> library(batchelor)
> B1 <- matrix(rnorm(10000, -1), ncol=50) # Batch 1 
> B2 <- matrix(rnorm(10000, 1), ncol=50) # Batch 2
> out <- fastMNN(B1, B2)
Warning in (function (A, nv = 5, nu = nv, maxit = 1000, work = nv + 7, reorth = TRUE,  :
  You're computing too large a percentage of total singular values, use a standard svd instead.
> out
class: SingleCellExperiment 
dim: 200 100 
metadata(2): merge.info pca.info
assays(1): reconstructed
rownames: NULL
rowData names(1): rotation
colnames: NULL
colData names(1): batch
reducedDimNames(1): corrected
mainExpName: NULL
altExpNames(0):
> assay(out)
Error in (function (cond)  : 
  error in evaluating the argument 'x' in selecting a method for function 'type': object of type 'S4' is not subsettable

> str(assay(out, withDimnames=FALSE))
Formal class 'LowRankMatrix' [package "BiocSingular"] with 1 slot
  ..@ seed:Formal class 'LowRankMatrixSeed' [package "BiocSingular"] with 2 slots
  .. .. ..@ rotation  : num [1:200, 1:50] -0.0622 -0.0752 -0.0614 -0.0641 -0.0696 ...
  .. .. ..@ components: num [1:100, 1:50] 0.709 0.706 0.71 0.709 0.707 ...

Here is my session info:

R version 4.3.1 (2023-06-16 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 11 x64 (build 22631)

Matrix products: default


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

time zone: Europe/Brussels
tzcode source: internal

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

other attached packages:
 [1] batchelor_1.16.0            SingleCellExperiment_1.22.0 SummarizedExperiment_1.30.2
 [4] Biobase_2.60.0              GenomicRanges_1.52.1        GenomeInfoDb_1.36.4        
 [7] IRanges_2.34.1              S4Vectors_0.38.2            BiocGenerics_0.46.0        
[10] MatrixGenerics_1.12.3       matrixStats_1.2.0          

loaded via a namespace (and not attached):
 [1] Matrix_1.6-4              compiler_4.3.1            crayon_1.5.2             
 [4] Rcpp_1.0.11               rsvd_1.0.5                scuttle_1.10.3           
 [7] bitops_1.0-7              DelayedMatrixStats_1.22.6 parallel_4.3.1           
[10] BiocParallel_1.34.2       lattice_0.22-5            XVector_0.40.0           
[13] S4Arrays_1.0.6            ScaledMatrix_1.8.1        igraph_1.6.0             
[16] DelayedArray_0.26.7       GenomeInfoDbData_1.2.10   rlang_1.1.2              
[19] BiocNeighbors_1.18.0      cli_3.6.2                 magrittr_2.0.3           
[22] BiocSingular_1.16.0       zlibbioc_1.46.0           grid_4.3.1               
[25] rstudioapi_0.15.0         irlba_2.3.5.1             sparseMatrixStats_1.12.2 
[28] lifecycle_1.0.4           codetools_0.2-19          ResidualMatrix_1.10.0    
[31] beachmat_2.16.0           abind_1.4-5               RCurl_1.98-1.13          
[34] pkgconfig_2.0.3           tools_4.3.1              

Thank you in advance for your time and consideration. :)

[LTLA]

I have no such problems with running example(fastMNN):

> example(fastMNN)

fstMNN> B1 <- matrix(rnorm(10000, -1), ncol=50) # Batch 1 

fstMNN> B2 <- matrix(rnorm(10000, 1), ncol=50) # Batch 2

fstMNN> out <- fastMNN(B1, B2)
Warning in (function (A, nv = 5, nu = nv, maxit = 1000, work = nv + 7, reorth = TRUE,  :
  You're computing too large a percentage of total singular values, use a standard svd instead.

fstMNN> # Corrected values for use in clustering, etc.
fstMNN> str(reducedDim(out)) 
 num [1:100, 1:50] -0.715 -0.71 -0.71 -0.71 -0.706 ...

fstMNN> # Extracting corrected expression values for gene 10.
fstMNN> summary(assay(out)[10,])
     Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
-0.163524 -0.070971 -0.037425 -0.040175 -0.008362  0.063427 

I will note that you are one BioC release behind, based on the version numbers in your session information. Perhaps try updating to the latest BioC release. (That said, I didn't change anything in any of the affected packages between releases, so I don't know whether this would really help; but you'd want to update anyway, because if there really is a problem, I'll only be updating the latest release, and not any of the older releases.)

[moosa-r]

Thanks for your time. Strange indeed.