Error in simpleLoess(y, x, w, span, degree = degree, parametric = parametric, : NA/NaN/Inf in foreign function call (arg 2)

[IrinaVKuznetsova]

The input raw count matrix has negative values. The core of the problem was introduced by the cell bender v0.3.0-v0.3.1
discussion broadinstitute/CellBender#306

Hi,

I am using Seurat 5, parsing h5 files generated with Cell Bender and creating a Seurat object with count matrices ( 8 samples - 8 count matrices) , which are stored as layers in Seurat 5. When I run FindVariableFeatures() function I am getting an error, which is inconsistent it occurs for different samples. So sometimes it raises for sample S25 another time it manages S25, but occurs in another sample S45, or L55 etc.

Never had this error before, and also checked:
#2387 suggested solution doesn't help as I Normalise data and also do DefaultAssay(object = cell_bender_seurat_filt) <- "RNA"

cell_bender_seurat
An object of class Seurat
36601 features across 48313 samples within 1 assay
Active assay: RNA (36601 features, 0 variable features)
16 layers present: counts.L25, counts.S25, counts.L39, counts.S39, counts.L45, counts.S45, counts.L55, counts.S55,

table([email protected]$orig.ident)
L25 L39 L45 L55 S25 S39 S45 S55
8108 6323 7189 5514 2100 6180 8620 4279 # sum=48313

code:
# parse cell bender h5
cell_bender_merged <- Read_CellBender_h5_Multi_Directory(
    base_path = PATH,
    custom_name = "_feature_bc_matrix_filtered.h5",                #25L_cellbender_feature_bc_matrix_filtered.h5
    sample_names = c("l25", "s25", "l39", "s39", "l45", "s45", "l55", "s55"), 
    merge = FALSE)
# create a list
cell_bender_list = list(L25=cell_bender_merged$l25, S25=cell_bender_merged$s25, 
                        L39=cell_bender_merged$l39, S39=cell_bender_merged$s39,
                        L45=cell_bender_merged$l45, S45=cell_bender_merged$s45, 
                        L55=cell_bender_merged$l55, S55=cell_bender_merged$s55)
# create a Seurat object
cell_bender_seurat <- CreateSeuratObject( counts = cell_bender_list,
                                          names.field = 2,              
                                          names.delim = '_' )
# filter
cell_bender_seurat_filt =subset(cell_bender_seurat, subset= nFeature_RNA > gene_thr_min & nFeature_RNA < gene_thr_max  & percent.mt < mito_thr & percent.ribo < ribo_thr)

cell_bender_seurat_filt<- NormalizeData(object = cell_bender_seurat_filt, normalization.method = "LogNormalize", scale.factor = 10000)
cell_bender_seurat_filt
An object of class Seurat
36601 features across 48313 samples within 1 assay
Active assay: RNA (36601 features, 0 variable features)
 16 layers present: counts.L25, counts.S25, counts.L39, counts.S39, counts.L45, counts.S45, counts.L55, counts.S55, data.L25, data.S25, data.L39, data.S39, data.L45, data.S45, data.L55, data.S55

DefaultAssay(object = cell_bender_seurat_filt) <- "RNA"
cell_bender_seurat_filt<- FindVariableFeatures(cell_bender_seurat_filt, selection.method = "vst", nfeatures = 1000)



Sample S25:
Error in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  :
  NA/NaN/Inf in foreign function call (arg 2)


or

Sample: S45
Error in simpleLoess(y, x, w, span, degree = degree, parametric = parametric,  :
  NA/NaN/Inf in foreign function call (arg 2)
In addition: Warning messages:
1: In eval(predvars, data, env) : NaNs produced
2: In hvf.info$variance.expected[not.const] <- 10^fit$fitted :
  number of items to replace is not a multiple of replacement length
3: In eval(predvars, data, env) : NaNs produced

sessionInfo()
R version 4.3.2 (2023-10-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS/LAPACK: /data/0_Tools/miniforge3/envs/PDX_manuscript23_v2/lib/libopenblasp-r0.3.26.so; LAPACK version 3.12.0

locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C

time zone: Etc/UTC
tzcode source: system (glibc)

attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base

other attached packages:
[1] patchwork_1.2.0 scCustomize_2.0.1
[3] hdf5r_1.3.9 djvdj_0.1.0
[5] SeuratWrappers_0.3.4 R.utils_2.12.3
[7] R.oo_1.26.0 R.methodsS3_1.8.2
[9] devtools_2.4.5 usethis_2.2.2
[11] scater_1.30.1 scuttle_1.12.0
[13] scDblFinder_1.16.0 SingleCellExperiment_1.24.0
[15] SummarizedExperiment_1.32.0 Biobase_2.62.0
[17] GenomicRanges_1.54.1 GenomeInfoDb_1.38.6
[19] IRanges_2.36.0 S4Vectors_0.40.2
[21] BiocGenerics_0.48.1 MatrixGenerics_1.14.0
[23] matrixStats_1.2.0 Matrix_1.6-5
[25] lubridate_1.9.3 forcats_1.0.0
[27] stringr_1.5.1 dplyr_1.1.4
[29] purrr_1.0.2 readr_2.1.5
[31] tidyr_1.3.1 tibble_3.2.1
[33] ggplot2_3.4.4 tidyverse_2.0.0
[35] WriteXLS_6.5.0 Seurat_5.0.1
[37] SeuratObject_5.0.1 sp_2.1-3
[39] pheatmap_1.0.12 remotes_2.4.2.1

loaded via a namespace (and not attached):
[1] fs_1.6.3 spatstat.sparse_3.0-3
[3] bitops_1.0-7 httr_1.4.7
[5] RColorBrewer_1.1-3 profvis_0.3.8
[7] tools_4.3.2 sctransform_0.4.1
[9] utf8_1.2.4 R6_2.5.1
[11] lazyeval_0.2.2 uwot_0.1.16
[13] urlchecker_1.0.1 withr_3.0.0
[15] gridExtra_2.3 progressr_0.14.0
[17] cli_3.6.2 spatstat.explore_3.2-6
[19] fastDummies_1.7.3 spatstat.data_3.0-4
[21] ggridges_0.5.6 pbapply_1.7-2
[23] Rsamtools_2.18.0 parallelly_1.37.0
[25] sessioninfo_1.2.2 limma_3.58.1
[27] shape_1.4.6 generics_0.1.3
[29] BiocIO_1.12.0 ica_1.0-3
[31] spatstat.random_3.2-2 ggbeeswarm_0.7.2
[33] fansi_1.0.6 abind_1.4-5
[35] lifecycle_1.0.4 yaml_2.3.8
[37] edgeR_4.0.15 snakecase_0.11.1
[39] SparseArray_1.2.4 Rtsne_0.17
[41] paletteer_1.6.0 grid_4.3.2
[43] promises_1.2.1 dqrng_0.3.2
[45] crayon_1.5.2 miniUI_0.1.1.1
[47] lattice_0.22-5 beachmat_2.18.1
[49] cowplot_1.1.3 pillar_1.9.0
[51] metapod_1.10.1 rjson_0.2.21
[53] xgboost_2.0.3.1 future.apply_1.11.1
[55] codetools_0.2-19 leiden_0.4.3.1
[57] glue_1.7.0 data.table_1.15.0
[59] vctrs_0.6.5 png_0.1-8
[61] spam_2.10-0 gtable_0.3.4
[63] rematch2_2.1.2 cachem_1.0.8
[65] S4Arrays_1.2.0 mime_0.12
[67] survival_3.5-8 statmod_1.5.0
[69] bluster_1.12.0 ellipsis_0.3.2
[71] fitdistrplus_1.1-11 ROCR_1.0-11
[73] nlme_3.1-164 bit64_4.0.5
[75] RcppAnnoy_0.0.22 irlba_2.3.5.1
[77] vipor_0.4.7 KernSmooth_2.23-22
[79] colorspace_2.1-0 ggrastr_1.0.2
[81] tidyselect_1.2.0 bit_4.0.5
[83] compiler_4.3.2 BiocNeighbors_1.20.2
[85] DelayedArray_0.28.0 plotly_4.10.4
[87] rtracklayer_1.62.0 scales_1.3.0
[89] lmtest_0.9-40 digest_0.6.34
[91] goftest_1.2-3 spatstat.utils_3.0-4
[93] XVector_0.42.0 htmltools_0.5.7
[95] pkgconfig_2.0.3 sparseMatrixStats_1.14.0
[97] fastmap_1.1.1 GlobalOptions_0.1.2
[99] rlang_1.1.3 htmlwidgets_1.6.4
[101] shiny_1.8.0 DelayedMatrixStats_1.24.0
[103] zoo_1.8-12 jsonlite_1.8.8
[105] BiocParallel_1.36.0 BiocSingular_1.18.0
[107] RCurl_1.98-1.14 magrittr_2.0.3
[109] GenomeInfoDbData_1.2.11 dotCall64_1.1-1
[111] munsell_0.5.0 Rcpp_1.0.12
[113] viridis_0.6.5 reticulate_1.35.0
[115] stringi_1.8.3 zlibbioc_1.48.0
[117] MASS_7.3-60.0.1 plyr_1.8.9
[119] pkgbuild_1.4.3 parallel_4.3.2
[121] listenv_0.9.1 ggrepel_0.9.5
[123] deldir_2.0-2 Biostrings_2.70.2
[125] splines_4.3.2 tensor_1.5
[127] circlize_0.4.15 hms_1.1.3
[129] locfit_1.5-9.8 igraph_1.6.0
[131] spatstat.geom_3.2-8 RcppHNSW_0.6.0
[133] reshape2_1.4.4 ScaledMatrix_1.10.0
[135] pkgload_1.3.4 XML_3.99-0.16.1
[137] scran_1.30.2 BiocManager_1.30.22
[139] ggprism_1.0.4 tzdb_0.4.0
[141] httpuv_1.6.14 RANN_2.6.1
[143] polyclip_1.10-6 future_1.33.1
[145] scattermore_1.2 janitor_2.2.0
[147] rsvd_1.0.5 xtable_1.8-4
[149] restfulr_0.0.15 RSpectra_0.16-1
[151] later_1.3.2 viridisLite_0.4.2
[153] memoise_2.0.1 beeswarm_0.4.0
[155] GenomicAlignments_1.38.2 cluster_2.1.6
[157] timechange_0.3.0 globals_0.16.2

[kulansam]

Hi @IrinaVKuznetsova , I am facing the same issue.

Have you find the solution?