Error with the vignette data with version seurat v5 (Error: unable to find an inherited method for function 'gsva')

[tetsy2]

Hello all,

Thanks for creating this tool, it looks greate. I have installed the version from the github (also from bioconductor, and same problem) in R 4.4 and I cannot reproduce the vignette data (it is also not working with my data):

devtools::install_github("ncborcherding/escape")
library(escape)
pbmc_small <- get("pbmc_small")
GS.hallmark <- getGeneSets(library = "H")
enrichment.scores <- escape.matrix(pbmc_small,
gene.sets = GS.hallmark,
groups = 1000,
min.size = 5)

[1] "Using sets of 1000 cells. Running 1 times."
Error: unable to find an inherited method for function 'gsva' for signature 'expr = "missing", gset.idx.list = "missing"'

Forcing method ssGSEA is also not working:

enrichment.scores <- escape.matrix(pbmc_small,

•                                gene.sets = GS.hallmark, 
  

•                                groups = 1000, 
  

•                                min.size = 5,method='ssGSEA')
  

Same error. However, it works if method is 'UCell'

How can I solve it? Thanks!

[ncborcherding]

This is an issue with your GSVA - pleas check out #88

Thanks,
Nick

[tetsy2]

Hello Nick,

Sorry to insist, but I uninstall and reinstall using the repo and the error still exists.

devtools::install_github("ncborcherding/escape")
devtools::install_github("rcastelo/GSVA")
library(escape)
library(GSVA)
library(Seurat)
pbmc_small <- get("pbmc_small")
GS.hallmark <- getGeneSets(library = "H")
enrichment.scores <- escape.matrix(pbmc_small,
gene.sets = GS.hallmark,
groups = 1000,
min.size = 5)

R version 4.4.0 (2024-04-24)
Platform: x86_64-apple-darwin20
Running under: macOS Sonoma 14.1.2

loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.22 splines_4.4.0
[3] later_1.3.2 tibble_3.2.1
[5] R.oo_1.26.0 polyclip_1.10-6
[7] graph_1.82.0 XML_3.99-0.16.1
[9] fastDummies_1.7.3 lifecycle_1.0.4
[11] globals_0.16.3 lattice_0.22-6
[13] MASS_7.3-60.2 ggdist_3.3.2
[15] magrittr_2.0.3 plotly_4.10.4
[17] rmarkdown_2.27 yaml_2.3.8
[19] httpuv_1.6.15 sctransform_0.4.1
[21] spam_2.10-0 spatstat.sparse_3.0-3
[23] reticulate_1.37.0 cowplot_1.1.3
[25] pbapply_1.7-2 DBI_1.2.3
[27] RColorBrewer_1.1-3 abind_1.4-5
[29] zlibbioc_1.50.0 Rtsne_0.17
[31] GenomicRanges_1.56.0 purrr_1.0.2
[33] R.utils_2.12.3 BiocGenerics_0.50.0
[35] msigdbr_7.5.1 GenomeInfoDbData_1.2.12
[37] IRanges_2.38.0 S4Vectors_0.42.0
[39] ggrepel_0.9.5 irlba_2.3.5.1
[41] spatstat.utils_3.0-4 listenv_0.9.1
[43] goftest_1.2-3 RSpectra_0.16-1
[45] spatstat.random_3.2-3 annotate_1.82.0
[47] fitdistrplus_1.1-11 parallelly_1.37.1
[49] DelayedMatrixStats_1.26.0 leiden_0.4.3.1
[51] codetools_0.2-20 DelayedArray_0.30.1
[53] tidyselect_1.2.1 UCSC.utils_1.0.0
[55] UCell_2.8.0 ScaledMatrix_1.12.0
[57] spatstat.explore_3.2-7 matrixStats_1.3.0
[59] stats4_4.4.0 jsonlite_1.8.8
[61] BiocNeighbors_1.22.0 progressr_0.14.0
[63] ggridges_0.5.6 survival_3.7-0
[65] tools_4.4.0 ica_1.0-3
[67] Rcpp_1.0.12 glue_1.7.0
[69] gridExtra_2.3 SparseArray_1.4.8
[71] xfun_0.44 MatrixGenerics_1.16.0
[73] distributional_0.4.0 GenomeInfoDb_1.40.1
[75] AUCell_1.26.0 dplyr_1.1.4
[77] HDF5Array_1.32.0 withr_3.0.0
[79] fastmap_1.2.0 rhdf5filters_1.16.0
[81] fansi_1.0.6 ggpointdensity_0.1.0
[83] digest_0.6.35 rsvd_1.0.5
[85] R6_2.5.1 mime_0.12
[87] colorspace_2.1-0 scattermore_1.2
[89] tensor_1.5 spatstat.data_3.0-4
[91] RSQLite_2.3.7 R.methodsS3_1.8.2
[93] utf8_1.2.4 tidyr_1.3.1
[95] generics_0.1.3 data.table_1.15.4
[97] httr_1.4.7 htmlwidgets_1.6.4
[99] S4Arrays_1.4.1 uwot_0.2.2
[101] pkgconfig_2.0.3 gtable_0.3.5
[103] blob_1.2.4 lmtest_0.9-40
[105] SingleCellExperiment_1.26.0 XVector_0.44.0
[107] htmltools_0.5.8.1 dotCall64_1.1-1
[109] GSEABase_1.66.0 scales_1.3.0
[111] Biobase_2.64.0 png_0.1-8
[113] knitr_1.47 rstudioapi_0.16.0
[115] reshape2_1.4.4 nlme_3.1-165
[117] cachem_1.1.0 zoo_1.8-12
[119] rhdf5_2.48.0 stringr_1.5.1
[121] KernSmooth_2.23-24 parallel_4.4.0
[123] miniUI_0.1.1.1 AnnotationDbi_1.66.0
[125] pillar_1.9.0 grid_4.4.0
[127] vctrs_0.6.5 RANN_2.6.1
[129] promises_1.3.0 BiocSingular_1.20.0
[131] beachmat_2.20.0 xtable_1.8-4
[133] cluster_2.1.6 evaluate_0.23
[135] cli_3.6.2 compiler_4.4.0
[137] rlang_1.1.4 crayon_1.5.2
[139] future.apply_1.11.2 plyr_1.8.9
[141] stringi_1.8.4 deldir_2.0-4
[143] viridisLite_0.4.2 BiocParallel_1.38.0
[145] babelgene_22.9 munsell_0.5.1
[147] Biostrings_2.72.1 lazyeval_0.2.2
[149] spatstat.geom_3.2-9 Matrix_1.7-0
[151] RcppHNSW_0.6.0 patchwork_1.2.0
[153] sparseMatrixStats_1.16.0 bit64_4.0.5
[155] future_1.33.2 ggplot2_3.5.1
[157] Rhdf5lib_1.26.0 KEGGREST_1.44.0
[159] shiny_1.8.1.1 SummarizedExperiment_1.34.0
[161] ROCR_1.0-11 igraph_2.0.3
[163] memoise_2.0.1 bit_4.0.5

[ncborcherding]

@tetsy2 - It doesn't look like your last post has the GSVA or escape version info. My guess based on the code you provided, is that you need to restart your R session before trying to run escape.

Nick