gianfilippo
commented
2 months ago UPDATE:
I reran the steps with the data from the tutorial and it works........something must have gone wrong converting from Seurat.
Closed gianfilippo closed 2 months ago
gianfilippo
commented
2 months ago UPDATE:
I reran the steps with the data from the tutorial and it works........something must have gone wrong converting from Seurat.
Hi,
I am running top_markers on a cds object converted from Seurat
I am following the tutorial rerunning dimensional reduciton cds <- reduce_dimension(cds) cds <- cluster_cells(cds) marker_test_res <- top_markers(cds, group_cells_by="cluster",reference_cells=1000,verbose=T)
Aggregating gene expression values for groups Error in names(sf) <- colnames(SingleCellExperiment::counts(cds)) : attempt to set an attribute on NULL
can you please help ?
Thanks
traceback() 5: size_factors(cds) 4: normalized_counts(cds, norm_method = norm_method, pseudocount = pseudocount) 3: aggregate_gene_expression(cds, cell_group_df = cell_group_df, norm_method = "size_only", scale_agg_values = FALSE) 2: as.matrix(aggregate_gene_expression(cds, cell_group_df = cell_group_df, norm_method = "size_only", scale_agg_values = FALSE)) 1: top_markers(cds, group_cells_by = "functional.cluster", reference_cells = 1000, verbose = T)
sessionInfo(): sessionInfo() R version 4.3.0 (2023-04-21) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux 8.8 (Ootpa)
Matrix products: default BLAS/LAPACK: FlexiBLAS OPENBLAS; LAPACK version 3.10.1
locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: America/New_York tzcode source: system (glibc)
attached base packages: [1] parallel grid stats4 stats graphics grDevices utils
[8] datasets methods base
other attached packages: [1] doMC_1.3.8 iterators_1.0.14
[3] foreach_1.5.2 STACAS_2.2.0
[5] SignacX_2.2.5 dsb_1.0.3
[7] SoupX_1.6.2 nat.utils_0.6.1
[9] clustree_0.5.0 ggraph_2.2.1
[11] HGNChelper_0.8.1 ProjecTILs_3.1.3
[13] DoubletFinder_2.0.3 scDblFinder_1.14.0
[15] djvdj_0.1.0 scater_1.28.0
[17] scuttle_1.14.0 muscat_1.18.0
[19] CIPR_0.1.0 ComplexHeatmap_2.16.0
[21] gprofiler2_0.2.3 cowplot_1.1.1
[23] future_1.32.0 purrr_1.0.2
[25] openxlsx_4.2.5.2 miQC_1.8.0
[27] SeuratDisk_0.0.0.9021 glmGamPoi_1.12.2
[29] dplyr_1.1.4 magrittr_2.0.3
[31] patchwork_1.2.0.9000 ggplot2_3.5.0.9000
[33] SeuratWrappers_0.3.1 panc8.SeuratData_3.0.2
[35] SeuratData_0.2.2 SeuratObject_4.1.3
[37] Seurat_4.3.0.1 monocle3_1.3.7
[39] SingleCellExperiment_1.24.0 SummarizedExperiment_1.30.2 [41] GenomicRanges_1.52.0 GenomeInfoDb_1.36.1
[43] IRanges_2.34.1 S4Vectors_0.38.2
[45] MatrixGenerics_1.15.0 matrixStats_1.1.0
[47] Biobase_2.60.0 BiocGenerics_0.46.0
loaded via a namespace (and not attached): [1] R.methodsS3_1.8.2 progress_1.2.2
[3] nnet_7.3-18 goftest_1.2-3
[5] Biostrings_2.68.1 TH.data_1.1-2
[7] vctrs_0.6.4 spatstat.random_3.1-5
[9] proxy_0.4-27 digest_0.6.31
[11] png_0.1-8 shape_1.4.6
[13] ggrepel_0.9.3 deldir_2.0-4
[15] parallelly_1.36.0 MASS_7.3-59
[17] reshape2_1.4.4 httpuv_1.6.9
[19] withr_3.0.0 ellipsis_0.3.2
[21] survival_3.5-5 memoise_2.0.1
[23] ggbeeswarm_0.7.2 emmeans_1.8.5
[25] zoo_1.8-12 GlobalOptions_0.1.2
[27] gtools_3.9.4 pbapply_1.7-0
[29] R.oo_1.26.0 prettyunits_1.1.1
[31] promises_1.2.0.1 httr_1.4.5
[33] restfulr_0.0.15 globals_0.16.2
[35] fitdistrplus_1.1-11 miniUI_0.1.1.1
[37] generics_0.1.3 zlibbioc_1.46.0
[39] ScaledMatrix_1.10.0 polyclip_1.10-4
[41] GenomeInfoDbData_1.2.10 xtable_1.8-4
[43] stringr_1.5.1 pracma_2.4.2
[45] doParallel_1.0.17 S4Arrays_1.2.0
[47] hms_1.1.3 irlba_2.3.5.1
[49] colorspace_2.1-0 hdf5r_1.3.10
[51] ROCR_1.0-11 reticulate_1.37.0.9000
[53] spatstat.data_3.0-1 flexmix_2.3-19
[55] lmtest_0.9-40 readr_2.1.4
[57] later_1.3.0 viridis_0.6.2
[59] modeltools_0.2-23 lattice_0.21-8
[61] spatstat.geom_3.2-4 future.apply_1.11.0
[63] scattermore_1.2 XML_3.99-0.16.1
[65] RcppAnnoy_0.0.21 pillar_1.9.0
[67] nlme_3.1-162 caTools_1.18.2
[69] compiler_4.3.0 beachmat_2.16.0
[71] stringi_1.7.12 tensor_1.5
[73] minqa_1.2.5 GenomicAlignments_1.36.0 [75] plyr_1.8.9 crayon_1.5.2
[77] abind_1.4-5 BiocIO_1.10.0
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[101] lme4_1.1-35.5 listenv_0.9.0
[103] DelayedMatrixStats_1.22.6 Rdpack_2.4
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[107] Matrix_1.5-4 statmod_1.5.0
[109] tzdb_0.3.0 tweenr_2.0.3
[111] pkgconfig_2.0.3 pheatmap_1.0.12
[113] tools_4.3.0 cachem_1.0.7
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[117] viridisLite_0.4.1 numDeriv_2016.8-1.1
[119] fastmap_1.1.1 scales_1.3.0
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[125] coda_0.19-4 BiocManager_1.30.21.1
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[131] yaml_2.3.7 rtracklayer_1.60.0
[133] cli_3.6.1 UCell_2.6.2
[135] leiden_0.4.3 lifecycle_1.0.3
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[139] mvtnorm_1.1-3 bluster_1.10.0
[141] backports_1.4.1 BiocParallel_1.36.0
[143] gtable_0.3.3 rjson_0.2.21
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[147] limma_3.56.2 jsonlite_1.8.4
[149] edgeR_3.42.4 bitops_1.0-7
[151] assertthat_0.2.1 bit64_4.0.5
[153] xgboost_1.7.5.1 Rtsne_0.16
[155] spatstat.utils_3.0-3 BiocNeighbors_1.18.0
[157] zip_2.3.1 metapod_1.8.0
[159] dqrng_0.3.0 ggtrace_0.2.0
[161] R.utils_2.12.3 pbkrtest_0.5.2
[163] lazyeval_0.2.2 shiny_1.7.4
[165] htmltools_0.5.5 sctransform_0.3.5
[167] rappdirs_0.3.3 glue_1.6.2
[169] XVector_0.40.0 RCurl_1.98-1.12
[171] mclust_6.0.0 scran_1.28.2
[173] gridExtra_2.3 EnvStats_2.7.0
[175] boot_1.3-28.1 igraph_2.0.3
[177] variancePartition_1.30.2 TMB_1.9.4
[179] R6_2.5.1 tidyr_1.3.0
[181] DESeq2_1.40.2 gplots_3.1.3
[183] labeling_0.4.2 cluster_2.1.4
[185] nloptr_2.0.3 DelayedArray_0.26.7
[187] tidyselect_1.2.1 vipor_0.4.5
[189] ggforce_0.4.2 rsvd_1.0.5
[191] munsell_0.5.0 KernSmooth_2.23-20
[193] data.table_1.14.8 htmlwidgets_1.6.2
[195] RColorBrewer_1.1-3 rlang_1.1.3
[197] spatstat.sparse_3.0-2 spatstat.explore_3.2-1
[199] lmerTest_3.1-3 remotes_2.4.2
[201] fansi_1.0.4 beeswarm_0.4.0