PDSpredict(testData): Error: Calling gsva(expr=., gset.idx.list=., method=., ...) is defunct; use a method-specific parameter object (see '?gsva').
mdu4003 opened this issue · 7 comments
Hello,
I want to use PDSpredict with one of my RNAseq, but this error shows when I try the test data:
library(PDSclassifier)
pds_calls <- PDSpredict(testData, species = 'human', threshold = 0.6)
Calculating ssGSEA scores...
Error: Calling gsva(expr=., gset.idx.list=., method=., ...) is defunct; use a method-specific parameter object (see '?gsva').
Would you mind letting me know how to solve it, please?
Thank you very much.
This is my configuration:
sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-apple-darwin20 (64-bit)
Running under: macOS Sonoma 14.3.1
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] PDSclassifier_1.0.0 escape_1.12.0 BiocManager_1.30.23
loaded via a namespace (and not attached):
[1] UCell_2.6.2 rstudioapi_0.16.0 magrittr_2.0.3 magick_2.8.3 fs_1.6.4
[6] zlibbioc_1.48.2 vctrs_0.6.5 memoise_2.0.1 RCurl_1.98-1.14 htmltools_0.5.8.1
[11] S4Arrays_1.2.1 usethis_2.2.3 curl_5.2.1 BiocNeighbors_1.20.2 broom_1.0.6
[16] Rhdf5lib_1.24.2 SparseArray_1.2.4 rhdf5_2.46.1 htmlwidgets_1.6.4 desc_1.4.3
[21] plyr_1.8.9 cachem_1.1.0 mime_0.12 lifecycle_1.0.4 pkgconfig_2.0.3
[26] rsvd_1.0.5 Matrix_1.6-5 R6_2.5.1 fastmap_1.2.0 GenomeInfoDbData_1.2.11
[31] MatrixGenerics_1.14.0 shiny_1.8.1.1 digest_0.6.35 colorspace_2.1-0 patchwork_1.2.0
[36] AnnotationDbi_1.64.1 S4Vectors_0.40.2 ps_1.7.6 irlba_2.3.5.1 pkgload_1.3.4
[41] GenomicRanges_1.54.1 RSQLite_2.3.6 beachmat_2.18.1 fansi_1.0.6 httr_1.4.7
[46] abind_1.4-5 compiler_4.3.2 remotes_2.5.0 withr_3.0.0 bit64_4.0.5
[51] backports_1.5.0 BiocParallel_1.36.0 DBI_1.2.2 pkgbuild_1.4.4 HDF5Array_1.30.1
[56] DelayedArray_0.28.0 sessioninfo_1.2.2 rjson_0.2.21 tools_4.3.2 httpuv_1.6.15
[61] msigdbr_7.5.1 glue_1.7.0 callr_3.7.6 rhdf5filters_1.14.1 promises_1.3.0
[66] grid_4.3.2 reshape2_1.4.4 generics_0.1.3 gtable_0.3.5 tidyr_1.3.1
[71] data.table_1.15.99 BiocSingular_1.18.0 ScaledMatrix_1.10.0 utf8_1.2.4 XVector_0.42.0
[76] BiocGenerics_0.48.1 pillar_1.9.0 stringr_1.5.1 babelgene_22.9 GSVA_1.53.2
[81] limma_3.58.1 later_1.3.2 dplyr_1.1.4 lattice_0.22-6 bit_4.0.5
[86] annotate_1.80.0 tidyselect_1.2.1 SingleCellExperiment_1.24.0 locfit_1.5-9.9 Biostrings_2.70.3
[91] miniUI_0.1.1.1 IRanges_2.36.0 edgeR_4.0.16 SummarizedExperiment_1.32.0 stats4_4.3.2
[96] Biobase_2.62.0 statmod_1.5.0 devtools_2.4.5 matrixStats_1.3.0 stringi_1.8.4
[101] codetools_0.2-20 tibble_3.2.1 graph_1.80.0 cli_3.6.2 xtable_1.8-4
[106] munsell_0.5.1 processx_3.8.4 Rcpp_1.0.12 GenomeInfoDb_1.38.8 png_0.1-8
[111] XML_3.99-0.16.1 parallel_4.3.2 ellipsis_0.3.2 ggplot2_3.5.1 blob_1.2.4
[116] profvis_0.3.8 urlchecker_1.0.1 sparseMatrixStats_1.14.0 bitops_1.0-7 SpatialExperiment_1.12.0
[121] GSEABase_1.64.0 scales_1.3.0 ggridges_0.5.6 purrr_1.0.2 crayon_1.5.2
[126] rlang_1.1.3 KEGGREST_1.42.0
I think you need to modify the line 50 in PDSpredict.R that reads like:
ssGSEA
y <- GSVA::gsva(x, c2.geneset, max.sz = Inf, ## min.size default as it may lead to no gene set scores
verbose = F, method = "ssgsea", parallel.sz = 4,
ssgsea.norm = F)
And substitute for this:
ssGSEA
x <- ssgseaParam( x, c2.geneset, assay = NA_character_, annotation = NA_character_, minSize = 1, maxSize = Inf,
alpha = 0.25,
normalize = FALSE
)
y <- gsva(x)
Hi @mdu4003, thanks so much for your message and input. We are planning to get around this and have updated PDSclassifier made available as soon as possible.
Hi @mdu4003 , I have now updated the PDSclassifier package. However, within this calculateSMI() for single-cell is not functional right now due to dependency package function issue within escape package, which I will update once it has been addressed.
Hope that helps. Let me know if you run into problem again.