runEscape: unable to find an inherited method for function 'gsva' for signature '"missing", "missing"'

[Diennguyen8290]

Hi,

Thanks for developing the tool.

I've tried to run the test for runEscape() using the example in the package help as below:

GS <- list(Bcells = c("MS4A1", "CD79B", "CD79A", "IGH1", "IGH2"), Tcells = c("CD3E", "CD3D", "CD3G", "CD7","CD8A")) pbmc_small <- SeuratObject::pbmc_small pbmc_small <- runEscape(pbmc_small, gene.sets = GS, min.size = NULL)

And get this error:

"Error in (function (classes, fdef, mtable) : unable to find an inherited method for function 'gsva' for signature '"missing", "missing"'"

The error is same for other geneset/seurat object.

Please could you help me have a look.

Many thanks.

Kind regards, Dien

p/s: Here is my session info: R version 4.3.2 (2023-10-31) Platform: aarch64-apple-darwin20 (64-bit) Running under: macOS Sonoma 14.4.1 Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0

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/London tzcode source: internal

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

other attached packages: [1] escape_1.99.1 Seurat_5.0.1 SeuratObject_5.0.1 sp_2.1-2

loaded via a namespace (and not attached): [1] RcppAnnoy_0.0.21 splines_4.3.2
[3] later_1.3.2 bitops_1.0-7
[5] tibble_3.2.1 R.oo_1.26.0
[7] polyclip_1.10-6 graph_1.80.0
[9] XML_3.99-0.16.1 fastDummies_1.7.3
[11] lifecycle_1.0.4 globals_0.16.2
[13] lattice_0.22-5 MASS_7.3-60.0.1
[15] ggdist_3.3.2 magrittr_2.0.3
[17] plotly_4.10.4 rmarkdown_2.25
[19] yaml_2.3.8 httpuv_1.6.13
[21] sctransform_0.4.1 spam_2.10-0
[23] spatstat.sparse_3.0-3 reticulate_1.34.0
[25] cowplot_1.1.3 pbapply_1.7-2
[27] DBI_1.2.0 RColorBrewer_1.1-3
[29] abind_1.4-5 zlibbioc_1.48.0
[31] Rtsne_0.17 GenomicRanges_1.54.1
[33] purrr_1.0.2 R.utils_2.12.3
[35] msigdbr_7.5.1 BiocGenerics_0.48.1
[37] RCurl_1.98-1.14 GenomeInfoDbData_1.2.11
[39] IRanges_2.36.0 S4Vectors_0.40.2
[41] ggrepel_0.9.5 irlba_2.3.5.1
[43] listenv_0.9.0 spatstat.utils_3.0-4
[45] GSVA_1.50.5 goftest_1.2-3
[47] RSpectra_0.16-1 spatstat.random_3.2-2
[49] annotate_1.80.0 fitdistrplus_1.1-11
[51] parallelly_1.36.0 DelayedMatrixStats_1.24.0
[53] leiden_0.4.3.1 codetools_0.2-19
[55] DelayedArray_0.28.0 tidyselect_1.2.0
[57] farver_2.1.1 UCell_2.6.2
[59] ScaledMatrix_1.10.0 matrixStats_1.2.0
[61] stats4_4.3.2 spatstat.explore_3.2-5
[63] jsonlite_1.8.8 BiocNeighbors_1.20.2
[65] ellipsis_0.3.2 progressr_0.14.0
[67] ggridges_0.5.6 survival_3.5-7
[69] tools_4.3.2 ica_1.0-3
[71] Rcpp_1.0.12 glue_1.7.0
[73] gridExtra_2.3 SparseArray_1.2.3
[75] xfun_0.41 distributional_0.4.0
[77] MatrixGenerics_1.14.0 GenomeInfoDb_1.38.5
[79] AUCell_1.24.0 HDF5Array_1.30.0
[81] dplyr_1.1.4 withr_3.0.0
[83] fastmap_1.1.1 ggpointdensity_0.1.0
[85] rhdf5filters_1.14.1 fansi_1.0.6
[87] rsvd_1.0.5 digest_0.6.34
[89] R6_2.5.1 mime_0.12
[91] colorspace_2.1-0 scattermore_1.2
[93] tensor_1.5 spatstat.data_3.0-4
[95] RSQLite_2.3.5 R.methodsS3_1.8.2
[97] utf8_1.2.4 tidyr_1.3.0
[99] generics_0.1.3 data.table_1.14.10
[101] httr_1.4.7 htmlwidgets_1.6.4
[103] S4Arrays_1.2.0 uwot_0.1.16
[105] pkgconfig_2.0.3 gtable_0.3.4
[107] blob_1.2.4 lmtest_0.9-40
[109] SingleCellExperiment_1.24.0 XVector_0.42.0
[111] htmltools_0.5.7 dotCall64_1.1-1
[113] GSEABase_1.64.0 scales_1.3.0
[115] Biobase_2.62.0 png_0.1-8
[117] knitr_1.45 rstudioapi_0.15.0
[119] reshape2_1.4.4 nlme_3.1-164
[121] rhdf5_2.46.1 zoo_1.8-12
[123] cachem_1.0.8 stringr_1.5.1
[125] KernSmooth_2.23-22 parallel_4.3.2
[127] miniUI_0.1.1.1 AnnotationDbi_1.64.1
[129] pillar_1.9.0 grid_4.3.2
[131] vctrs_0.6.5 RANN_2.6.1
[133] promises_1.2.1 BiocSingular_1.18.0
[135] beachmat_2.18.0 xtable_1.8-4
[137] cluster_2.1.6 evaluate_0.23
[139] cli_3.6.2 compiler_4.3.2
[141] rlang_1.1.3 crayon_1.5.2
[143] future.apply_1.11.1 labeling_0.4.3
[145] plyr_1.8.9 stringi_1.8.3
[147] viridisLite_0.4.2 deldir_2.0-2
[149] BiocParallel_1.36.0 babelgene_22.9
[151] munsell_0.5.0 Biostrings_2.70.2
[153] lazyeval_0.2.2 spatstat.geom_3.2-7
[155] Matrix_1.6-5 RcppHNSW_0.5.0
[157] patchwork_1.2.0.9000 sparseMatrixStats_1.14.0
[159] bit64_4.0.5 future_1.33.1
[161] Rhdf5lib_1.24.1 ggplot2_3.5.1
[163] KEGGREST_1.42.0 shiny_1.8.0
[165] highr_0.10 SummarizedExperiment_1.32.0 [167] ROCR_1.0-11 igraph_2.0.1.1
[169] memoise_2.0.1 bit_4.0.5

[ncborcherding]

Hey Dien,

Thanks for reaching out - the issue arises from the update in the GSVA R package. You can install the compatible version for escape using: https://www.bioconductor.org/packages/release/bioc/html/GSVA.html

Please let me know if you gave any other questions.

Nick

[Diennguyen8290]

Hi Nick @ncborcherding,

Thanks for your swift reply.

May I ask which version of GSVA would work best for the package please?

I've tried with GSVA 1.50.5, 1.52.0 and 1.52.2 (the most recent one), but nothing worked.

Thank you, Dien

[ncborcherding]

The new method for GSVA/ssGSEA calling was implemented in v1.51.5. If you have installed v1.52.0 or 1.52.2 - this should work. I would make sure you restart your R session before re-trying escape. That is usually the issue for these persistent version problems.

Nick

[Diennguyen8290]

Thanks, Nick.

I've installed it on another version of R and it seems to work well with GSVA 1.4.

Thank you for your time and help.

Dien

[ncborcherding]

Thanks for following up and posting your solution.

Nick