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Error in `.rowNamesDF<-`(x, value = value) : duplicate 'row.names' are not allowed
Dear colleagues,
I'm facing a new error I don't know how to overcome. I'm currently trying to load this dataset https://cells.ucsc.edu/?ds=ext-mouse-atlas in R using get_ucsc_reference()
but it returns this error :
[100%] Downloaded 47242005 bytes...
[100%] Downloaded 3246770440 bytes...
Error in `.rowNamesDF<-`(x, value = value) :
duplicate 'row.names' are not allowed
Can you help me to solve this issue please ? This is the code I'm using :
library(clustifyr)
mouse.embryo.ref <- get_ucsc_reference(cb_url = "https://cells.ucsc.edu/?ds=ext-mouse-atlas",
cluster_col = "celltype_extended_atlas",
if_log = FALSE)
And this is my sessionInfo()
:
R version 4.1.3 (2022-03-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8 LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8 LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel grid stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] org.Mm.eg.db_3.14.0 AnnotationDbi_1.56.2 biomaRt_2.57.1 ggrepel_0.9.3 TCC_1.34.0 ROC_1.70.0 baySeq_2.28.0
[8] abind_1.4-5 edgeR_3.36.0 limma_3.50.3 DESeq2_1.34.0 enrichR_3.2 plotly_4.10.2 VennDiagram_1.7.3
[15] futile.logger_1.4.3 gprofiler2_0.2.2 viper_1.28.0 dorothea_1.7.3 RColorBrewer_1.1-3 slingshot_2.2.1 TrajectoryUtils_1.2.0
[22] princurve_2.1.6 heatmap3_1.1.9 singleseqgset_0.1.2.9000 Matrix_1.5-4.1 msigdbr_7.5.1 splatter_1.18.2 SingleCellExperiment_1.16.0
[29] SummarizedExperiment_1.24.0 Biobase_2.54.0 GenomicRanges_1.46.1 GenomeInfoDb_1.30.1 IRanges_2.28.0 S4Vectors_0.32.4 BiocGenerics_0.40.0
[36] MatrixGenerics_1.6.0 matrixStats_1.0.0 pheatmap_1.0.12 tidyr_1.3.0 tibble_3.2.1 decoupleR_2.5.2 ggplot2_3.4.2
[43] stringr_1.5.0 DT_0.28 clustifyr_1.13.1 patchwork_1.1.2 SeuratObject_4.1.3 Seurat_4.3.0.1 dplyr_1.1.2
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 scattermore_1.2 R.methodsS3_1.8.2 bit64_4.0.5 knitr_1.43 R.utils_2.12.2 irlba_2.3.5.1 DelayedArray_0.20.0 data.table_1.14.8
[10] KEGGREST_1.34.0 RCurl_1.98-1.12 generics_0.1.3 cowplot_1.1.1 lambda.r_1.2.4 RSQLite_2.3.1 RANN_2.6.1 proxy_0.4-27 future_1.33.0
[19] bit_4.0.5 spatstat.data_3.0-1 xml2_1.3.5 httpuv_1.6.11 xfun_0.39 hms_1.1.3 babelgene_22.9 evaluate_0.21 promises_1.2.0.1
[28] fansi_1.0.4 progress_1.2.2 dbplyr_2.3.3 igraph_1.5.0 DBI_1.1.3 geneplotter_1.72.0 htmlwidgets_1.6.2 spatstat.geom_3.2-2 purrr_1.0.1
[37] ellipsis_0.3.2 crosstalk_1.2.0 backports_1.4.1 annotate_1.72.0 deldir_1.0-9 vctrs_0.6.3 ROCR_1.0-11 entropy_1.3.1 cachem_1.0.8
[46] withr_2.5.0 progressr_0.13.0 checkmate_2.2.0 sctransform_0.3.5 prettyunits_1.1.1 goftest_1.2-3 cluster_2.1.4 segmented_1.6-4 lazyeval_0.2.2
[55] crayon_1.5.2 genefilter_1.76.0 spatstat.explore_3.2-1 labeling_0.4.2 pkgconfig_2.0.3 nlme_3.1-162 rlang_1.1.1 globals_0.16.2 lifecycle_1.0.3
[64] miniUI_0.1.1.1 filelock_1.0.2 BiocFileCache_2.2.1 polyclip_1.10-4 lmtest_0.9-40 zoo_1.8-12 ggridges_0.5.4 png_0.1-8 viridisLite_0.4.2
[73] rjson_0.2.21 bitops_1.0-7 R.oo_1.25.0 KernSmooth_2.23-21 Biostrings_2.62.0 blob_1.2.4 parallelly_1.36.0 spatstat.random_3.1-5 scales_1.2.1
[82] memoise_2.0.1 magrittr_2.0.3 plyr_1.8.8 ica_1.0-3 zlibbioc_1.40.0 compiler_4.1.3 fitdistrplus_1.1-11 cli_3.6.1 XVector_0.34.0
[91] listenv_0.9.0 pbapply_1.7-2 formatR_1.14 MASS_7.3-60 tidyselect_1.2.0 stringi_1.7.12 yaml_2.3.7 locfit_1.5-9.8 bcellViper_1.30.0
[100] fastmatch_1.1-3 tools_4.1.3 future.apply_1.11.0 rstudioapi_0.14 gridExtra_2.3 farver_2.1.1 Rtsne_0.16 digest_0.6.32 shiny_1.7.4.1
[109] Rcpp_1.0.11 later_1.3.1 RcppAnnoy_0.0.21 WriteXLS_6.4.0 httr_1.4.7 kernlab_0.9-32 colorspace_2.1-0 XML_3.99-0.14 tensor_1.5
[118] reticulate_1.30 splines_4.1.3 uwot_0.1.16 spatstat.utils_3.0-3 sp_2.0-0 xtable_1.8-4 jsonlite_1.8.7 futile.options_1.0.1 R6_2.5.1
[127] pillar_1.9.0 htmltools_0.5.5 mime_0.12 glue_1.6.2 fastmap_1.1.1 BiocParallel_1.34.2 class_7.3-22 codetools_0.2-19 fgsea_1.26.0
[136] utf8_1.2.3 lattice_0.21-8 spatstat.sparse_3.0-2 mixtools_2.0.0 curl_5.0.2 leiden_0.4.3 survival_3.5-5 rmarkdown_2.23 munsell_0.5.0
[145] e1071_1.7-13 fastcluster_1.2.3 GenomeInfoDbData_1.2.7 reshape2_1.4.4 gtable_0.3.3
Thank you
Paul
It looks like they provide the matrix in a tar.gz format which our code does not support. I would recommend downloading their scanpy or anndata object and generating the average clusters using scanpy, or converting to an R object for use with Seurat or Singlecellexperiment.