Error in test_classfier() #14
Description
Hello,
Thank you very much for developing this great package! I am trying to generate a classifier for detecting CD4 T cells in my data using a custom classifier I created with train_classifier(). However, I am running into issues with the test_classifier() and classify_cells() functions. I am using Seurat5 objects for this analysis as well. Any assistance would be greatly appreciated! The error output is below:
classifier_top100_logFC_cd4_test <- test_classifier(classifier = classifier_top100_logFC_cd4, test_obj = query, assay = "RNA",tag_slot = 'CD4_T_Cell')
Error in `dplyr::mutate()`:
ℹ In argument: `class = apply(...)`.
Caused by error in `if (x[1] >= thres) ...`:
! missing value where TRUE/FALSE needed
Run `rlang::last_trace()` to see where the error occurred.
Warning message:
In method$prob(modelFit = modelFit, newdata = newdata, submodels = param) :
kernlab class probability calculations failed; returning NAs
rlang::last_trace(drop = FALSE)
<error/dplyr:::mutate_error>
Error in `dplyr::mutate()`:
ℹ In argument: `class = apply(...)`.
Caused by error in `if (x[1] >= thres) ...`:
! missing value where TRUE/FALSE needed
---
Backtrace:
▆
1. ├─scAnnotatR::test_classifier(...)
2. ├─scAnnotatR::test_classifier(...)
3. │ └─scAnnotatR:::test_classifier_seurat(...)
4. │ └─scAnnotatR:::test_classifier_from_mat(...)
5. │ └─scAnnotatR:::test_performance(test_mat, classifier, test_tag)
6. │ └─... %>% ...
7. ├─dplyr::mutate(...)
8. ├─dplyr:::mutate.data.frame(...)
9. │ └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
10. │ ├─base::withCallingHandlers(...)
11. │ └─dplyr:::mutate_col(dots[[i]], data, mask, new_columns)
12. │ └─mask$eval_all_mutate(quo)
13. │ └─dplyr (local) eval()
14. ├─base::apply(...)
15. │ └─scAnnotatR (local) FUN(newX[, i], ...)
16. └─base::.handleSimpleError(...)
17. └─dplyr (local) h(simpleError(msg, call))
18. └─rlang::abort(message, class = error_class, parent = parent, call = error_call)
sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8 LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] scAnnotatR_1.0.0 tidytext_0.4.1 ggrepel_0.9.4 caret_6.0-94 lattice_0.20-45 dplyr_1.1.3 ggpubr_0.6.0 ggsci_3.0.0 BPCells_0.1.0
[10] ggplot2_3.4.4 SingleCellExperiment_1.16.0 SummarizedExperiment_1.24.0 Biobase_2.54.0 GenomicRanges_1.46.1 GenomeInfoDb_1.30.1 IRanges_2.28.0 S4Vectors_0.32.4 BiocGenerics_0.40.0
[19] MatrixGenerics_1.6.0 matrixStats_1.0.0 reticulate_1.34.0 Seurat_4.9.9.9067 SeuratObject_4.9.9.9091 sp_2.1-1 SeuratDisk_0.0.0.9020
loaded via a namespace (and not attached):
[1] utf8_1.2.3 spatstat.explore_3.2-3 tidyselect_1.2.0 RSQLite_2.3.4 AnnotationDbi_1.56.2 htmlwidgets_1.6.2 grid_4.1.2 Rtsne_0.16 pROC_1.18.5
[10] munsell_0.5.0 codetools_0.2-18 ica_1.0-3 future_1.33.0 miniUI_0.1.1.1 withr_2.5.1 spatstat.random_3.1-6 colorspace_2.1-0 progressr_0.14.0
[19] filelock_1.0.3 rstudioapi_0.15.0 ROCR_1.0-11 ggsignif_0.6.4 tensor_1.5 listenv_0.9.0 GenomeInfoDbData_1.2.7 polyclip_1.10-6 bit64_4.0.5
[28] parallelly_1.36.0 vctrs_0.6.4 generics_0.1.3 ipred_0.9-14 timechange_0.2.0 BiocFileCache_2.2.1 R6_2.5.1 hdf5r_1.3.8 DelayedArray_0.20.0
[37] bitops_1.0-7 spatstat.utils_3.0-3 cachem_1.0.8 promises_1.2.1 scales_1.2.1 nnet_7.3-17 gtable_0.3.4 globals_0.16.2 goftest_1.2-3
[46] spam_2.9-1 timeDate_4032.109 rlang_1.1.1 splines_4.1.2 rstatix_0.7.2 lazyeval_0.2.2 ModelMetrics_1.2.2.2 broom_1.0.5 spatstat.geom_3.2-5
[55] BiocManager_1.30.22 yaml_2.3.7 reshape2_1.4.4 abind_1.4-5 backports_1.4.1 httpuv_1.6.11 tokenizers_0.3.0 tools_4.1.2 lava_1.7.3
[64] ellipsis_0.3.2 RColorBrewer_1.1-3 proxy_0.4-27 ggridges_0.5.4 Rcpp_1.0.11 plyr_1.8.9 zlibbioc_1.40.0 purrr_1.0.2 RCurl_1.98-1.13
[73] rpart_4.1.16 deldir_1.0-9 pbapply_1.7-2 cowplot_1.1.1 zoo_1.8-12 cluster_2.1.2 magrittr_2.0.3 data.table_1.14.8 RSpectra_0.16-1
[82] scattermore_1.2 lmtest_0.9-40 RANN_2.6.1 SnowballC_0.7.1 fitdistrplus_1.1-11 patchwork_1.1.3 mime_0.12 xtable_1.8-4 fastDummies_1.7.3
[91] gridExtra_2.3 compiler_4.1.2 tibble_3.2.1 KernSmooth_2.23-20 crayon_1.5.2 htmltools_0.5.6.1 later_1.3.1 tidyr_1.3.0 lubridate_1.9.3
[100] DBI_1.2.0 dbplyr_2.4.0 MASS_7.3-55 rappdirs_0.3.3 data.tree_1.1.0 car_3.1-2 Matrix_1.6-1.1 cli_3.6.1 parallel_4.1.2
[109] dotCall64_1.1-0 gower_1.0.1 igraph_1.5.1 pkgconfig_2.0.3 plotly_4.10.2 spatstat.sparse_3.0-2 recipes_1.0.9 foreach_1.5.2 hardhat_1.3.0
[118] XVector_0.34.0 prodlim_2023.08.28 janeaustenr_1.0.0 stringr_1.5.0 digest_0.6.33 sctransform_0.4.0 RcppAnnoy_0.0.21 spatstat.data_3.0-1 Biostrings_2.62.0
[127] leiden_0.4.3 uwot_0.1.16 curl_5.1.0 kernlab_0.9-32 shiny_1.7.5.1 lifecycle_1.0.3 nlme_3.1-155 jsonlite_1.8.7 carData_3.0-5
[136] viridisLite_0.4.2 fansi_1.0.5 pillar_1.9.0 KEGGREST_1.34.0 fastmap_1.1.1 httr_1.4.7 survival_3.2-13 interactiveDisplayBase_1.32.0 glue_1.6.2
[145] png_0.1-8 iterators_1.0.14 BiocVersion_3.14.0 bit_4.0.5 class_7.3-20 stringi_1.7.12 blob_1.2.4 RcppHNSW_0.5.0 AnnotationHub_3.2.2
[154] memoise_2.0.1 renv_1.0.3 e1071_1.7-14 ape_5.7-1 irlba_2.3.5.1 future.apply_1.11.0