Describe the bug
Error while running the perform_de() function
To Reproduce
Steps to reproduce the behavior:
- In R:
# Performing differential expression analysis following by impacted pathway analysis
sce_subset <- sce[, sce$clusters == 1]
#DE
result_de <- perform_de(
sce_subset,
mast_method = "glmer",
min_counts = 1,
min_cells_pc = 0.25,
dependent_var = "diagnosis",
ref_class = "Controls",
confounding_vars = c("cngeneson"),
random_effects_var = "manifest",
ensembl_mapping_file = ensembl_fp,
nAGQ = 0)
- See error:
── Starting Differential Gene Expression ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Pre-processing SingleCellExperiment ──
Selected 2284 from 9902 genes with >1 count(s) in >25% of cells.
→ Rescaling numeric variables
── Calculating variance explained by individual ──
→ Normalizing counts
→ Calculating variance explained by individual for 2284 genes
Error: BiocParallel errors
1 remote errors, element index: 1
0 unevaluated and other errors
first remote error:
Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.
Expected behavior
What is the workaround here? Not sure why this is happening. It seems like a specific issue with related to the data but not sure what it is. Any suggestion?
System
R version 4.2.3 (2023-03-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.6 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8
[6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] DT_0.32 plotly_4.10.4.9000 ggplot2_3.5.0 KernSmooth_2.23-20 fields_15.2
[6] viridisLite_0.4.2 spam_2.10-0 dplyr_1.1.4 SingleCellExperiment_1.20.1 SummarizedExperiment_1.28.0
[11] Biobase_2.58.0 GenomicRanges_1.50.2 GenomeInfoDb_1.34.9 IRanges_2.32.0 S4Vectors_0.36.2
[16] BiocGenerics_0.44.0 MatrixGenerics_1.10.0 matrixStats_1.2.0 scFlow_0.7.4 DoubletFinder_2.0.4
[21] EWCE_1.6.0 RNOmni_1.0.1.2 apcluster_1.4.11 lme4_1.1-35.1 Seurat_5.0.2
[26] SeuratObject_5.0.1 sp_2.1-3 irlba_2.3.5.1 Matrix_1.6-5
loaded via a namespace (and not attached):
[1] rsvd_1.0.5 ica_1.0-3 svglite_2.1.3 foreach_1.5.2 lmtest_0.9-40
[6] crayon_1.5.2 MASS_7.3-58.2 rhdf5filters_1.10.1 MAST_1.24.1 WriteXLS_6.5.0
[11] nlme_3.1-162 backports_1.4.1 monocle3_1.3.5 rlang_1.1.3 XVector_0.38.0
[16] bib2df_1.1.2.0 ROCR_1.0-11 nloptr_2.0.3 limma_3.54.2 scater_1.26.1
[21] filelock_1.0.3 stringfish_0.16.0 qs_0.25.7 BiocParallel_1.32.6 rjson_0.2.21
[26] bit64_4.0.5 glue_1.7.0 rngtools_1.5.2 sctransform_0.4.1 parallel_4.2.3
[31] vipor_0.4.7 spatstat.sparse_3.0-3 AnnotationDbi_1.60.2 UpSetR_1.4.0 HGNChelper_0.8.1
[36] dotCall64_1.1-1 spatstat.geom_3.2-9 tidyselect_1.2.0 fitdistrplus_1.1-11 XML_3.99-0.16.1
[41] tidyr_1.3.1 zoo_1.8-12 ggpubr_0.6.0 formattable_0.2.1 xtable_1.8-4
[46] RcppHNSW_0.6.0 magrittr_2.0.3 evaluate_0.23 scuttle_1.8.4 cli_3.6.2
[51] zlibbioc_1.44.0 rstudioapi_0.15.0 doRNG_1.8.6 miniUI_0.1.1.1 whisker_0.4.1
[56] bslib_0.6.1 treeio_1.22.0 rliger_1.0.1 fastDummies_1.7.3 maps_3.4.2
[61] shiny_1.8.0 xfun_0.42 BiocSingular_1.14.0 cluster_2.1.4 KEGGREST_1.38.0
[66] tibble_3.2.1 interactiveDisplayBase_1.36.0 ggrepel_0.9.5 threejs_0.3.3 ape_5.7-1
[71] listenv_0.9.1 Biostrings_2.66.0 png_0.1-8 future_1.33.1 withr_3.0.0
[76] bitops_1.0-7 plyr_1.8.9 dqrng_0.3.2 RcppParallel_5.1.7 pillar_1.9.0
[81] cachem_1.0.8 fs_1.6.3 hdf5r_1.3.9 paletteer_1.6.0 DelayedMatrixStats_1.20.0
[86] vctrs_0.6.5 ellipsis_0.3.2 generics_0.1.3 RApiSerialize_0.1.2 tools_4.2.3
[91] beeswarm_0.4.0 munsell_0.5.0 DelayedArray_0.24.0 fastmap_1.1.1 compiler_4.2.3
[96] abind_1.4-5 httpuv_1.6.14 ExperimentHub_2.6.0 ewceData_1.6.0 GenomeInfoDbData_1.2.9
[101] gridExtra_2.3 enrichR_3.2 edgeR_3.40.2 lattice_0.20-45 deldir_2.0-4
[106] utf8_1.2.4 later_1.3.2 prismatic_1.1.1 BiocFileCache_2.6.1 humaniformat_0.6.0
[111] jsonlite_1.8.8 kBET_0.99.6 scales_1.3.0 ScaledMatrix_1.6.0 tidytree_0.4.6
[116] pbapply_1.7-2 carData_3.0-5 sparseMatrixStats_1.10.0 lazyeval_0.2.2 promises_1.2.1
[121] car_3.1-2 doParallel_1.0.17 R.utils_2.12.3 goftest_1.2-3 spatstat.utils_3.0-4
[126] reticulate_1.35.0 rmarkdown_2.25 sandwich_3.1-0 cowplot_1.1.3 Rtsne_0.17
[131] forcats_1.0.0 uwot_0.1.16.9000 igraph_2.0.2 HDF5Array_1.26.0 survival_3.5-3
[136] yaml_2.3.8 systemfonts_1.0.5 htmltools_0.5.7 memoise_2.0.1 locfit_1.5-9.8
[141] digest_0.6.34 assertthat_0.2.1 mime_0.12 rappdirs_0.3.3 RSQLite_2.3.5
[146] yulab.utils_0.1.4 future.apply_1.11.1 orthogene_1.4.2 data.table_1.15.2 blob_1.2.4
[151] R.oo_1.26.0 preprocessCore_1.60.2 labeling_0.4.3 splines_4.2.3 Formula_1.2-5
[156] rematch2_2.1.2 Rhdf5lib_1.20.0 AnnotationHub_3.6.0 RCurl_1.98-1.14 broom_1.0.5
[161] hms_1.1.3 gprofiler2_0.2.3 base64enc_0.1-3 rhdf5_2.42.1 colorspace_2.1-0
[166] DropletUtils_1.18.1 BiocManager_1.30.22 WebGestaltR_0.4.6 ggbeeswarm_0.7.2 aplot_0.2.2
[171] maxLik_1.5-2 sass_0.4.8 mclust_6.1 Rcpp_1.0.12 RANN_2.6.1
[176] fansi_1.0.6 tzdb_0.4.0 parallelly_1.37.1 R6_2.5.1 grid_4.2.3
[181] ggridges_0.5.6 lifecycle_1.0.4 miscTools_0.6-28 curl_5.2.0 ggsignif_0.6.4
[186] minqa_1.2.6 jquerylib_0.1.4 leaflet_2.2.1 leiden_0.4.3.1 RcppAnnoy_0.0.22
[191] RColorBrewer_1.1-3 iterators_1.0.14 spatstat.explore_3.2-6 stringr_1.5.1 htmlwidgets_1.6.4
[196] beachmat_2.14.2 polyclip_1.10-6 biomaRt_2.54.1 purrr_1.0.2 crosstalk_1.2.1
[201] DirichletReg_0.7-1 gridGraphics_0.5-1 globals_0.16.2 patchwork_1.2.0 spatstat.random_3.2-3
[206] progressr_0.14.0 codetools_0.2-19 FNN_1.1.4 prettyunits_1.2.0 dbplyr_2.4.0
[211] RSpectra_0.16-1 R.methodsS3_1.8.2 gtable_0.3.4 DBI_1.2.2 highr_0.10
[216] ggfun_0.1.4 tensor_1.5 httr_1.4.7 stringi_1.8.3 progress_1.2.3
[221] farver_2.1.1 reshape2_1.4.4 english_1.2-6 viridis_0.6.5 ggtree_3.6.2
[226] xml2_1.3.6 ggdendro_0.2.0 boot_1.3-28.1 grr_0.9.5 BiocNeighbors_1.16.0
[231] readr_2.1.5 ggplotify_0.1.2 homologene_1.4.68.19.3.27 scattermore_1.2 BiocVersion_3.16.0
[236] bit_4.0.5 spatstat.data_3.0-4 pkgconfig_2.0.3 babelgene_22.9 rstatix_0.7.2
[241] knitr_1.45
Additional context
Add any other context about the problem here.
Describe the bug
Error while running the
perform_de()functionTo Reproduce
Steps to reproduce the behavior:
── Starting Differential Gene Expression ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────
── Pre-processing SingleCellExperiment ──
Selected 2284 from 9902 genes with >1 count(s) in >25% of cells.
→ Rescaling numeric variables
── Calculating variance explained by
individual──→ Normalizing counts
→ Calculating variance explained by
individualfor 2284 genesError: BiocParallel errors
1 remote errors, element index: 1
0 unevaluated and other errors
first remote error:
Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.
Expected behavior
What is the workaround here? Not sure why this is happening. It seems like a specific issue with related to the data but not sure what it is. Any suggestion?
System
Additional context
Add any other context about the problem here.