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20 hours ago •
satijalab
satijalab
Error in `rownames<-`(`*tmp*`, value = genes_step1) : attempt to set 'rownames' on an object with no dimensions
SCTransform gives me a very weird error for no apparent reason (data appears to be just fine, attached a reproducible slice).
Reproducible example: exp.rds.zip
exp <- readRDS("exp.rds")
data <- CreateSeuratObject(counts = exp,
project = "", min.cells = 0, min.features = 0)
data[["percent.mt"]] <- PercentageFeatureSet(data, pattern = "^MT-")
data <- subset(data, subset = nFeature_RNA > 200 & nFeature_RNA < 2500 & nCount_RNA < 20000 & percent.mt < 5)
data <- SCTransform(data, method = "glmGamPoi", vars.to.regress = "percent.mt", verbose = FALSE,
residual_type = "pearson")
Given error is:
Error in `rownames<-`(`*tmp*`, value = genes_step1) :
attempt to set 'rownames' on an object with no dimensions
My sessionInfo():
> sessionInfo() R version 3.6.1 (2019-07-05) Platform: x86_64-pc-linux-gnu (64-bit) Running under: CentOS release 6.7 (Final) Matrix products: default BLAS: /gfs/apps/apps/R-3.6.1/lib64/R/lib/libRblas.so LAPACK: /gfs/apps/apps/R-3.6.1/lib64/R/lib/libRlapack.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 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets methods base other attached packages: [1] Rcpp_1.0.3 SingleR_1.0.5 SummarizedExperiment_1.16.1 DelayedArray_0.12.2 BiocParallel_1.20.1 matrixStats_0.55.0 [7] Biobase_2.46.0 GenomicRanges_1.38.0 GenomeInfoDb_1.22.0 IRanges_2.20.2 S4Vectors_0.24.3 BiocGenerics_0.32.0 [13] Seurat_3.1.4 loaded via a namespace (and not attached): [1] AnnotationHub_2.18.0 BiocFileCache_1.10.2 sn_1.5-5 plyr_1.8.5 igraph_1.2.4.2 [6] lazyeval_0.2.2 splines_3.6.1 listenv_0.8.0 ggplot2_3.3.3 TH.data_1.0-10 [11] digest_0.6.29 htmltools_0.5.1.1 gdata_2.18.0 fansi_0.4.1 magrittr_2.0.1 [16] memoise_1.1.0 cluster_2.1.0 ROCR_1.0-7 globals_0.14.0 sandwich_2.5-1 [21] colorspace_1.4-1 blob_1.2.1 rappdirs_0.3.1 ggrepel_0.8.2 dplyr_1.0.6 [26] crayon_1.4.1 RCurl_1.98-1.1 jsonlite_1.7.2 survival_3.1-12 zoo_1.8-7 [31] ape_5.3 glue_1.4.2 gtable_0.3.0 zlibbioc_1.32.0 XVector_0.26.0 [36] leiden_0.3.3 future.apply_1.7.0 scales_1.1.0 mvtnorm_1.1-0 DBI_1.1.0 [41] bibtex_0.4.2.2 metap_1.3 plotrix_3.7-7 xtable_1.8-4 viridisLite_0.4.0 [46] reticulate_1.22-9000 bit_1.1-15.1 rsvd_1.0.3 tsne_0.1-3 htmlwidgets_1.5.1 [51] httr_1.4.2 gplots_3.0.3 RColorBrewer_1.1-2 TFisher_0.2.0 ellipsis_0.3.0 [56] ica_1.0-2 pkgconfig_2.0.3 uwot_0.1.8 dbplyr_2.1.1 utf8_1.1.4 [61] here_1.0.1 AnnotationDbi_1.48.0 later_1.0.0 tidyselect_1.1.1 rlang_0.4.11 [66] reshape2_1.4.3 munsell_0.5.0 BiocVersion_3.10.1 tools_3.6.1 generics_0.0.2 [71] RSQLite_2.2.0 ExperimentHub_1.12.0 ggridges_0.5.2 fastmap_1.0.1 stringr_1.4.0 [76] yaml_2.2.1 npsurv_0.4-0 bit64_0.9-7 fitdistrplus_1.0-14 caTools_1.18.0 [81] purrr_0.3.4 RANN_2.6.1 pbapply_1.4-2 future_1.21.0 nlme_3.1-140 [86] mime_0.9 compiler_3.6.1 plotly_4.9.2 curl_4.3 png_0.1-7 [91] interactiveDisplayBase_1.24.0 lsei_1.2-0 tibble_3.1.1 stringi_1.4.5 lattice_0.20-38 [96] Matrix_1.2-17 multtest_2.42.0 vctrs_0.3.8 mutoss_0.1-12 pillar_1.6.0 [101] lifecycle_1.0.0 BiocManager_1.30.10 Rdpack_0.11-1 lmtest_0.9-37 RcppAnnoy_0.0.16 [106] BiocNeighbors_1.4.2 data.table_1.12.8 cowplot_1.0.0 bitops_1.0-6 irlba_2.3.3 [111] gbRd_0.4-11 httpuv_1.5.2 patchwork_1.0.0 R6_2.4.1 promises_1.1.0 [116] KernSmooth_2.23-15 gridExtra_2.3 parallelly_1.22.0 codetools_0.2-16 MASS_7.3-51.4 [121] gtools_3.8.1 assertthat_0.2.1 rprojroot_2.0.2 sctransform_0.2.1 mnormt_1.5-6 [126] multcomp_1.4-12 GenomeInfoDbData_1.2.2 grid_3.6.1 tidyr_1.1.3 DelayedMatrixStats_1.8.0 [131] Rtsne_0.15 shiny_1.4.0 numDeriv_2016.8-1.1
Version with verbose=TRUE:
> data <- SCTransform(data, method = "glmGamPoi", vars.to.regress = "percent.mt", verbose = TRUE,
+ residual_type = "pearson")
Calculating cell attributes for input UMI matrix
Variance stabilizing transformation of count matrix of size 665 by 20
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 665 genes, 20 cells
|=============================================================================================================================================================================| 100%
Error in `rownames<-`(`*tmp*`, value = genes_step1) :
attempt to set 'rownames' on an object with no dimensions
Can you update to a more recent version of sctransform? I am unable to reproduce this with the latest version:
data <- SCTransform(data, method = "glmGamPoi")
Calculating cell attributes from input UMI matrix: log_umi
Variance stabilizing transformation of count matrix of size 665 by 20
Model formula is y ~ log_umi
Get Negative Binomial regression parameters per gene
Using 665 genes, 20 cells
|==============================================================================| 100%
Found 28 outliers - those will be ignored in fitting/regularization step
Second step: Get residuals using fitted parameters for 665 genes
|==============================================================================| 100%
Computing corrected count matrix for 665 genes
|==============================================================================| 100%
Calculating gene attributes
Wall clock passed: Time difference of 1.5068 secs
Determine variable features
Place corrected count matrix in counts slot
Centering data matrix
|==============================================================================| 100%
Set default assay to SCT
Closing due to inactivity. Feel free to reopen if you are still facing issues.