Error in `fn()`: ! Cannot add new cells with [[<-

[boluofen]

Hello, my code run into this issue, can you give me some advice to solve this?
geneNMF.programs<-multiNMF(sce,assay="RNA",slot="data",

•                        k=4:9,L1=c(0,0),center=TRUE,nfeatures=2000)
  

Error in fn():
! Cannot add new cells with [[<-
Run rlang::last_trace() to see where the error occurred.

[mass-a]

Hi, can you add more info? does this happen on the test dataset, or on your own data? what is your sessioninfo()?
Also, you may check if it is related to satijalab/seurat#8407

[boluofen]

It is my own data , a 10814 cells seurat
sessionInfo()
R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

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: Asia/Shanghai
tzcode source: system (glibc)

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

other attached packages:
[1] fgsea_1.26.0 msigdbr_7.5.1 GeneNMF_0.6.0 tidydr_0.0.5
[5] edgeR_3.42.4 limma_3.56.2 DESeq2_1.40.2 SummarizedExperiment_1.30.2
[9] MatrixGenerics_1.12.3 matrixStats_1.4.1 GenomicRanges_1.52.1 GenomeInfoDb_1.36.4
[13] future_1.34.0 COSG_0.9.0 org.Hs.eg.db_3.17.0 AnnotationDbi_1.62.2
[17] IRanges_2.34.1 S4Vectors_0.38.2 Biobase_2.60.0 BiocGenerics_0.46.0
[21] lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 purrr_1.0.2
[25] readr_2.1.5 tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0
[29] tidyr_1.3.1 dplyr_1.1.4 Seurat_5.1.0 SeuratObject_5.0.2
[33] sp_2.1-4 nichenetr_2.2.0

loaded via a namespace (and not attached):
[1] urlchecker_1.0.1 nnet_7.3-19 goftest_1.2-3 Biostrings_2.68.1
[5] vctrs_0.6.5 spatstat.random_3.3-2 digest_0.6.37 png_0.1-8
[9] shape_1.4.6.1 proxy_0.4-27 ggrepel_0.9.6 deldir_2.0-4
[13] parallelly_1.38.0 RcppML_0.3.7 MASS_7.3-60.0.1 reshape2_1.4.4
[17] httpuv_1.6.15 foreach_1.5.2 withr_3.0.1 xfun_0.48
[21] ggfun_0.1.5 ggpubr_0.6.0 ellipsis_0.3.2 survival_3.7-0
[25] memoise_2.0.1 profvis_0.3.8 zoo_1.8-12 GlobalOptions_0.1.2
[29] pbapply_1.7-2 Genshinpalette_0.0.1.9000 Formula_1.2-5 KEGGREST_1.40.1
[33] promises_1.3.0 httr_1.4.7 rstatix_0.7.2 globals_0.16.3
[37] fitdistrplus_1.2-1 ps_1.8.0 rstudioapi_0.16.0 GOplot_1.0.2
[41] miniUI_0.1.1.1 generics_0.1.3 processx_3.8.4 base64enc_0.1-3
[45] babelgene_22.9 curl_5.2.3 zlibbioc_1.46.0 polyclip_1.10-7
[49] randomForest_4.7-1.2 GenomeInfoDbData_1.2.10 xtable_1.8-4 desc_1.4.3
[53] doParallel_1.0.17 evaluate_1.0.1 S4Arrays_1.2.0 hms_1.1.3
[57] irlba_2.3.5.1 colorspace_2.1-1 visNetwork_2.1.2 ROCR_1.0-11
[61] reticulate_1.39.0 spatstat.data_3.1-2 magrittr_2.0.3 lmtest_0.9-40
[65] later_1.3.2 viridis_0.6.5 lattice_0.22-6 spatstat.geom_3.3-3
[69] future.apply_1.11.2 scattermore_1.2 shadowtext_0.1.4 cowplot_1.1.3
[73] RcppAnnoy_0.0.22 class_7.3-22 Hmisc_5.1-3 pillar_1.9.0
[77] nlme_3.1-165 iterators_1.0.14 caTools_1.18.3 compiler_4.3.1
[81] RSpectra_0.16-2 stringi_1.8.4 gower_1.0.1 tensor_1.5
[85] devtools_2.4.5 plyr_1.8.9 crayon_1.5.3 abind_1.4-8
[89] ggdendro_0.2.0 locfit_1.5-9.10 bit_4.5.0 fastmatch_1.1-4
[93] codetools_0.2-20 recipes_1.1.0 e1071_1.7-16 GetoptLong_1.0.5
[97] plotly_4.10.4 mime_0.12 splines_4.3.1 circlize_0.4.16
[101] Rcpp_1.0.13 fastDummies_1.7.4 knitr_1.48 blob_1.2.4
[105] utf8_1.2.4 clue_0.3-65 fs_1.6.4 listenv_0.9.1
[109] checkmate_2.3.2 pkgbuild_1.4.4 ggsignif_0.6.4 Matrix_1.6-5
[113] callr_3.7.6 tzdb_0.4.0 tweenr_2.0.3 pkgconfig_2.0.3
[117] pheatmap_1.0.12 tools_4.3.1 cachem_1.1.0 RSQLite_2.3.7
[121] viridisLite_0.4.2 DBI_1.2.3 fastmap_1.2.0 rmarkdown_2.28
[125] scales_1.3.0 grid_4.3.1 usethis_3.0.0 ica_1.0-3
[129] broom_1.0.7 patchwork_1.3.0 dotCall64_1.2 carData_3.0-5
[133] RANN_2.6.2 rpart_4.1.23 farver_2.1.2 DiagrammeR_1.0.11
[137] foreign_0.8-87 cli_3.6.3 leiden_0.4.3.1 lifecycle_1.0.4
[141] caret_6.0-94 uwot_0.2.2 lava_1.8.0 sessioninfo_1.2.2
[145] backports_1.5.0 BiocParallel_1.34.2 timechange_0.3.0 gtable_0.3.5
[149] rjson_0.2.23 ggridges_0.5.6 progressr_0.14.0 parallel_4.3.1
[153] pROC_1.18.5 SnowballC_0.7.1 jsonlite_1.8.9 RcppHNSW_0.6.0
[157] bitops_1.0-9 bit64_4.5.2 Rtsne_0.17 spatstat.utils_3.1-0
[161] spatstat.univar_3.0-1 timeDate_4041.110 lazyeval_0.2.2 shiny_1.9.1
[165] htmltools_0.5.8.1 sctransform_0.4.1 glue_1.8.0 spam_2.11-0
[169] XVector_0.40.0 RCurl_1.98-1.16 gridExtra_2.3 igraph_2.0.3
[173] R6_2.5.1 fdrtool_1.2.18 labeling_0.4.3 cluster_2.1.6
[177] pkgload_1.4.0 ipred_0.9-15 DelayedArray_0.26.7 tidyselect_1.2.1
[181] htmlTable_2.4.3 ggforce_0.4.2 car_3.1-3 ModelMetrics_1.2.2.2
[185] munsell_0.5.1 KernSmooth_2.23-24 data.table_1.16.0 htmlwidgets_1.6.4
[189] ComplexHeatmap_2.16.0 RColorBrewer_1.1-3 rlang_1.1.4 spatstat.sparse_3.1-0
[193] lsa_0.73.3 spatstat.explore_3.3-2 remotes_2.5.0 ggnewscale_0.5.0
[197] fansi_1.0.6 hardhat_1.4.0 prodlim_2024.06.25
Thanks

[mass-a]

It's difficult to guess the exact source of the error without a reproducible example, but I expect it could be related to the Seurat issue linked above, and stemming from subsetting a Seurat object with multiple layers. If your object has multiple layers, I would suggest to avoid using them (run JoinLayers() before any analysis), or even convert the assays from Assay5 to the Assay type, as detailed here.