Closed yecotoo closed 2 weeks ago
I am having the same issue. One of the new commits may have created this bug as Libra was working fine on my data a couple of months ago.
我遇到了同样的问题。其中一个新提交可能造成了这个错误,因为几个月前 Libra 对我的数据运行良好。
I agree! I run it well last week, but met the error these days after update! I checked my data many times, found nothing wrong
Hi all, can you provide the full error log for tracing here? Also, are you able to run the Libra on the toy data without error?
library(Libra)
library(Seurat)
data(hagai_toy)
res = Libra::run_de(hagai_toy)
Hi all, can you provide the full error log for tracing here? Also, are you able to run the Libra on the toy data without error?
library(Libra) library(Seurat) data(hagai_toy) res = Libra::run_de(hagai_toy)
library(Seurat) data(hagai_toy) res = Libra::run_de(hagai_toy) Error in h(simpleError(msg, call)): Error in calculating parameter "x" when selecting method for function "rowSums": subscript out of bounds In addition: Warning message: Layer ‘data' is empty. Not work, Still meet the error! Some thing may wrong in the code you provided
Hi, can you provide the sessionInfo()
? In particular the Seurat version?
Hi, can you provide the
sessionInfo()
? In particular the Seurat version?
sessionInfo() R version 4.4.1 (2024-06-14 ucrt) Platform: x86_64-w64-mingw32/x64 Running under: Windows 11 x64 (build 22631)
Matrix products: default
locale: [1] LC_COLLATE=Chinese (Simplified)_China.utf8 LC_CTYPE=Chinese (Simplified)_China.utf8 LC_MONETARY=Chinese (Simplified)_China.utf8 LC_NUMERIC=C LC_TIME=Chinese (Simplified)_China.utf8
time zone: Asia/Shanghai tzcode source: internal
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] Libra_1.0.0 Seurat_5.1.0 SeuratObject_5.0.2 sp_2.1-4
loaded via a namespace (and not attached):
[1] RcppAnnoy_0.0.22 splines_4.4.1 later_1.3.2 tibble_3.2.1 polyclip_1.10-7 fastDummies_1.7.4 lifecycle_1.0.4 pbmcapply_1.5.1
[9] edgeR_4.2.1 globals_0.16.3 processx_3.8.4 lattice_0.22-6 MASS_7.3-61 magrittr_2.0.3 limma_3.60.4 plotly_4.10.4
[17] remotes_2.5.0 httpuv_1.6.15 sctransform_0.4.1 spam_2.10-0 sessioninfo_1.2.2 pkgbuild_1.4.4 spatstat.sparse_3.1-0 reticulate_1.38.0
[25] cowplot_1.1.3 pbapply_1.7-2 minqa_1.2.8 RColorBrewer_1.1-3 abind_1.4-5 pkgload_1.4.0 zlibbioc_1.50.0 glmmTMB_1.1.9
[33] Rtsne_0.17 GenomicRanges_1.56.1 purrr_1.0.2 BiocGenerics_0.50.0 msigdbr_7.5.1 GenomeInfoDbData_1.2.12 IRanges_2.38.1 S4Vectors_0.42.1
[41] ggrepel_0.9.5 irlba_2.3.5.1 listenv_0.9.1 spatstat.utils_3.1-0 pheatmap_1.0.12 goftest_1.2-3 RSpectra_0.16-2 spatstat.random_3.3-1
[49] fitdistrplus_1.2-1 parallelly_1.38.0 leiden_0.4.3.1 codetools_0.2-20 DelayedArray_0.30.1 tidyselect_1.2.1 UCSC.utils_1.0.0 tester_0.2.0
[57] lme4_1.1-35.5 matrixStats_1.3.0 stats4_4.4.1 spatstat.explore_3.3-1 jsonlite_1.8.8 ellipsis_0.3.2 progressr_0.14.0 ggridges_0.5.6
[65] survival_3.7-0 tools_4.4.1 ica_1.0-3 Rcpp_1.0.13 blme_1.0-5 glue_1.7.0 gridExtra_2.3 SparseArray_1.4.8
[73] mgcv_1.9-1 DESeq2_1.44.0 MatrixGenerics_1.17.0 usethis_3.0.0 GenomeInfoDb_1.40.1 dplyr_1.1.4 numDeriv_2016.8-1.1 BiocManager_1.30.24
[81] fastmap_1.2.0 boot_1.3-30 fansi_1.0.6 callr_3.7.6 digest_0.6.36 R6_2.5.1 mime_0.12 colorspace_2.1-1
[89] scattermore_1.2 tensor_1.5 spatstat.data_3.1-2 utf8_1.2.4 tidyr_1.3.1 generics_0.1.3 data.table_1.15.4 httr_1.4.7
[97] htmlwidgets_1.6.4 S4Arrays_1.4.1 uwot_0.2.2 pkgconfig_2.0.3 gtable_0.3.5 lmtest_0.9-40 XVector_0.44.0 htmltools_0.5.8.1
[105] profvis_0.3.8 dotCall64_1.1-1 TMB_1.9.14 scales_1.3.0 Biobase_2.64.0 png_0.1-8 spatstat.univar_3.0-0 rstudioapi_0.16.0
[113] reshape2_1.4.4 nlme_3.1-166 curl_5.2.1 nloptr_2.1.1 cachem_1.1.0 zoo_1.8-12 stringr_1.5.1 KernSmooth_2.23-24
[121] parallel_4.4.1 miniUI_0.1.1.1 desc_1.4.3 pillar_1.9.0 grid_4.4.1 vctrs_0.6.5 RANN_2.6.1 urlchecker_1.0.1
[129] promises_1.3.0 xtable_1.8-4 cluster_2.1.6 cli_3.6.3 locfit_1.5-9.10 compiler_4.4.1 rlang_1.1.4 crayon_1.5.3
[137] future.apply_1.11.2 ps_1.7.7 forcats_1.0.0 plyr_1.8.9 fs_1.6.4 stringi_1.8.4 viridisLite_0.4.2 deldir_2.0-4
[145] BiocParallel_1.38.0 babelgene_22.9 lmerTest_3.1-3 munsell_0.5.1 lazyeval_0.2.2 devtools_2.4.5 spatstat.geom_3.3-2 Matrix_1.7-0
[153] RcppHNSW_0.6.0 patchwork_1.2.0 future_1.34.0 ggplot2_3.5.1 statmod_1.5.0 shiny_1.9.1 SummarizedExperiment_1.34.0 ROCR_1.0-11
[161] igraph_2.0.3 memoise_2.0.1
Hi, it should be fixed. Apologies for the bug.
Hi, it should be fixed. Apologies for the bug.
Thanks! Sorry for that, something new may occur, which I met before. This is an old problem. It occured now. I have checked my expr seuratObject, and meta, the colname is "cell_type". So I don't know why it can't identify my cell_type_col? What's the reason may be? Please give me a reply, thanks! libra_result = run_de(expr, meta = meta,
group_by()
:
! Must group by variables found in .data
.
✖ Column cell_type
is not found.
Run rlang::last_trace()
to see where the error occurred.
rlang::last_trace() <error/rlang_error> Error in
group_by()
: ! Must group by variables found in.data
. ✖ Columncell_type
is not found.Backtrace: ▆
- ├─Libra::run_de(...)
- │ └─... %>% ...
- ├─dplyr::rename(...)
- ├─dplyr::arrange(., cell_type, gene)
- ├─dplyr::ungroup(.)
- ├─dplyr::select(...)
- ├─dplyr::left_join(., out_stats, by = "gene")
- ├─dplyr::select(., -avg_logFC)
- ├─dplyr::mutate(., gene = as.character(gene))
- ├─dplyr::mutate(., p_val_adj = p.adjust(p_val, method = "BH"))
- ├─dplyr::group_by(., cell_type)
└─dplyr:::group_by.data.frame(., cell_type) Run rlang::last_trace(drop = FALSE) to see 2 hidden frames. rlang::last_trace(drop = FALSE) <error/rlang_error> Error in
group_by()
: ! Must group by variables found in.data
. ✖ Columncell_type
is not found.Backtrace: ▆
- ├─Libra::run_de(...)
- │ └─... %>% ...
- ├─dplyr::rename(...)
- ├─dplyr::arrange(., cell_type, gene)
- ├─dplyr::ungroup(.)
- ├─dplyr::select(...)
- ├─dplyr::left_join(., out_stats, by = "gene")
- ├─dplyr::select(., -avg_logFC)
- ├─dplyr::mutate(., gene = as.character(gene))
- ├─dplyr::mutate(., p_val_adj = p.adjust(p_val, method = "BH"))
- ├─dplyr::group_by(., cell_type)
- └─dplyr:::group_by.data.frame(., cell_type)
- └─dplyr::group_by_prepare(.data, ..., .add = .add, error_call = current_env())
- └─rlang::abort(bullets, call = error_call)
when I run: libra_result = run_de(expr, meta = meta, replicate_col = "orig.ident", cell_type_col = "cell_type", label_col = "seurat_clusters",
input_type = "scRNA",
I met a mistake: Error in h(simpleError(msg, call)): Error in calculating parameter "x" when selecting method for function "rowSums": subscript out of bounds In addition: Warning message: Layer ‘data' is empty. How to fix it? I Have checked my expr and meta, nothing was wrong, what the problem could be? I wonder. Thanks