Closed
Description
I'm having some issues with RunAzimuth. I originally had a larger Seurat object but I've included a 100-cell sample here that produces the same/similar error. cells100.rds.zip
library(Azimuth)
library(Seurat)
library(SeuratData)
# available_data <- AvailableData()
cells100 <- readRDS("cells100.rds")
DefaultAssay(cells100) <-"RNA"
pbmc_out <- RunAzimuth(cells100,assay="RNA", umap.name="umap", reference = "Seurat/Azimuth/pbmcref.SeuratData/inst/azimuth/")
bm_out <- RunAzimuth(cells100, assay="RNA", umap.name="umap", reference = "Seurat/Azimuth/bonemarrowref.SeuratData/inst/azimuth/")pbmc_out was generated successfully, but bm_out threw some errors. I'm sure each cell name is unique, and I'm not sure where that duplicate cell name would come from
Warning messages:
1: In RunUMAP.default(object = neighborlist, reduction.model = reduction.model, ... :
Number of neighbors between query and reference is not equal to the number of neighbors within reference
2: Cannot add objects with duplicate keys (offending key: UMAP_), setting key to 'ref.umap_'
3: non-unique value when setting 'row.names': ‘AGCCTAACATCACGTA-1_3’I'd really appreciate your guys' input here - thanks!
sessionInfo:
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS: /usr/lib64/libblas.so.3.4.2
LAPACK: /usr/lib64/liblapack.so.3.4.2
locale:
[1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8
[5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8 LC_PAPER=en_AU.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] Signac_1.7.0 SeuratData_0.2.2 Azimuth_0.4.6 shinyBS_0.61.1
[5] dittoSeq_1.8.1 ggpubr_0.4.0 ggsci_2.9 forcats_1.0.0
[9] stringr_1.5.0 dplyr_1.1.2 purrr_1.0.1 readr_2.1.2
[13] tidyr_1.3.0 tibble_3.2.1 ggplot2_3.4.2 tidyverse_1.3.1
[17] cowplot_1.1.1 DoubletFinder_2.0.3 DropletUtils_1.16.0 SingleCellExperiment_1.18.0
[21] SummarizedExperiment_1.28.0 Biobase_2.58.0 GenomicRanges_1.50.2 GenomeInfoDb_1.34.9
[25] IRanges_2.32.0 S4Vectors_0.36.2 BiocGenerics_0.44.0 MatrixGenerics_1.10.0
[29] matrixStats_1.0.0 patchwork_1.1.2.9000 SeuratObject_4.1.3 Seurat_4.3.0.1
loaded via a namespace (and not attached):
[1] shinydashboard_0.7.2 utf8_1.2.3 spatstat.explore_3.2-1 reticulate_1.30
[5] R.utils_2.12.2 ks_1.13.5 tidyselect_1.2.0 htmlwidgets_1.6.2
[9] grid_4.2.0 BiocParallel_1.32.6 Rtsne_0.16 munsell_0.5.0
[13] codetools_0.2-18 ica_1.0-3 DT_0.27 future_1.33.0
[17] miniUI_0.1.1.1 withr_2.5.0 spatstat.random_3.1-5 colorspace_2.1-0
[21] progressr_0.13.0 knitr_1.43 rstudioapi_0.14 ROCR_1.0-11
[25] ggsignif_0.6.3 tensor_1.5 listenv_0.9.0 GenomeInfoDbData_1.2.9
[29] polyclip_1.10-4 bit64_4.0.5 pheatmap_1.0.12 Nebulosa_1.8.0
[33] rhdf5_2.42.1 parallelly_1.36.0 vctrs_0.6.3 generics_0.1.3
[37] xfun_0.39 R6_2.5.1 locfit_1.5-9.7 hdf5r_1.3.5
[41] bitops_1.0-7 rhdf5filters_1.10.1 spatstat.utils_3.0-3 DelayedArray_0.24.0
[45] promises_1.2.0.1 scales_1.2.1 googlesheets4_1.0.0 rgeos_0.5-9
[49] gtable_0.3.3 beachmat_2.14.2 globals_0.16.2 goftest_1.2-3
[53] rlang_1.1.1 RcppRoll_0.3.0 splines_4.2.0 rstatix_0.7.0
[57] lazyeval_0.2.2 gargle_1.2.0 spatstat.geom_3.2-4 broom_1.0.4
[61] modelr_0.1.8 yaml_2.3.7 reshape2_1.4.4 abind_1.4-5
[65] backports_1.4.1 httpuv_1.6.11 SeuratDisk_0.0.0.9020 tools_4.2.0
[69] ellipsis_0.3.2 RColorBrewer_1.1-3 ggridges_0.5.4 Rcpp_1.0.11
[73] plyr_1.8.8 sparseMatrixStats_1.10.0 zlibbioc_1.44.0 RCurl_1.98-1.12
[77] deldir_1.0-9 pbapply_1.7-2 zoo_1.8-12 haven_2.5.0
[81] ggrepel_0.9.3 cluster_2.1.3 fs_1.6.3 magrittr_2.0.3
[85] data.table_1.14.8 scattermore_1.2 reprex_2.0.1 lmtest_0.9-40
[89] RANN_2.6.1 googledrive_2.0.0 mvtnorm_1.1-3 fitdistrplus_1.1-11
[93] shinyjs_2.1.0 hms_1.1.3 mime_0.12 evaluate_0.21
[97] xtable_1.8-4 readxl_1.4.0 mclust_5.4.10 gridExtra_2.3
[101] compiler_4.2.0 crayon_1.5.2 KernSmooth_2.23-20 R.oo_1.25.0
[105] htmltools_0.5.5 tzdb_0.4.0 later_1.3.1 lubridate_1.8.0
[109] DBI_1.1.3 dbplyr_2.3.2 rappdirs_0.3.3 MASS_7.3-57
[113] Matrix_1.5-4 car_3.0-13 cli_3.6.1 R.methodsS3_1.8.2
[117] parallel_4.2.0 igraph_1.5.0.1 pkgconfig_2.0.3 sp_2.0-0
[121] plotly_4.10.2 scuttle_1.6.2 spatstat.sparse_3.0-2 xml2_1.3.4
[125] dqrng_0.3.0 XVector_0.38.0 rvest_1.0.2 digest_0.6.33
[129] sctransform_0.3.5 RcppAnnoy_0.0.21 pracma_2.4.2 Biostrings_2.66.0
[133] spatstat.data_3.0-1 fastmatch_1.1-3 cellranger_1.1.0 rmarkdown_2.23
[137] leiden_0.4.3 uwot_0.1.16 edgeR_3.40.2 DelayedMatrixStats_1.20.0
[141] curl_5.0.1 Rsamtools_2.14.0 shiny_1.7.4.1 lifecycle_1.0.3
[145] nlme_3.1-157 jsonlite_1.8.7 Rhdf5lib_1.20.0 carData_3.0-5
[149] viridisLite_0.4.2 limma_3.54.2 fansi_1.0.4 pillar_1.9.0
[153] lattice_0.20-45 fastmap_1.1.1 httr_1.4.6 survival_3.3-1
[157] glue_1.6.2 png_0.1-8 bit_4.0.5 presto_1.0.0
[161] stringi_1.7.12 HDF5Array_1.26.0 irlba_2.3.5.1 future.apply_1.11.0