tumorscholar
commented
3 days ago @Arturron thank you for your advice, I use the HPC server with the below module, if you can provide more detail then I can ask our IT department to install it on the HPC server.
Hello Nick, Thank you again for making this wonderful tool. I am trying to use CoNGA Reduction on a Harmony-integrated Seurat V5 object. The script is unable to identify the data slot. Help please.
Error in CoNGA.dist(sc, features, assay[x]) : no slot of name "data" for this object of class "Assay5"Matrix products: default BLAS/LAPACK: /usr/lib64/libopenblasp-r0.3.3.so
locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C 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 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] viridis_0.6.5 viridisLite_0.4.2 Trex_0.99.11 tensorflow_2.16.0 reticulate_1.38.0 scRepertoire_2.0.5 [7] lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 readr_2.1.5
[13] tidyr_1.3.1 tibble_3.2.1 tidyverse_2.0.0 patchwork_1.2.0 ggplot2_3.5.1 Seurat_5.0.0
[19] SeuratObject_5.0.2 sp_2.1-4
loaded via a namespace (and not attached): [1] utf8_1.2.4 spatstat.explore_3.3-2 tidyselect_1.2.1 htmlwidgets_1.6.4
[5] grid_4.2.2 Rtsne_0.17 munsell_0.5.1 codetools_0.2-18
[9] ica_1.0-3 future_1.34.0 miniUI_0.1.1.1 withr_3.0.1
[13] keras_2.15.0 spatstat.random_3.3-1 colorspace_2.1-1 progressr_0.14.0
[17] Biobase_2.58.0 ggalluvial_0.12.5 rstudioapi_0.16.0 stats4_4.2.2
[21] SingleCellExperiment_1.20.1 ROCR_1.0-11 tensor_1.5 listenv_0.9.1
[25] MatrixGenerics_1.10.0 labeling_0.4.3 GenomeInfoDbData_1.2.9 polyclip_1.10-7
[29] farver_2.1.2 parallelly_1.38.0 vctrs_0.6.5 generics_0.1.3
[33] timechange_0.3.0 R6_2.5.1 GenomeInfoDb_1.34.9 graphlayouts_1.1.1
[37] VGAM_1.1-11 spatstat.univar_3.0-0 bitops_1.0-8 spatstat.utils_3.1-0
[41] cachem_1.1.0 DelayedArray_0.24.0 assertthat_0.2.1 promises_1.3.0
[45] scales_1.3.0 ggraph_2.2.1 gtable_0.3.5 globals_0.16.3
[49] goftest_1.2-3 spam_2.10-0 tidygraph_1.3.1 rlang_1.1.4
[53] MatrixModels_0.5-3 zeallot_0.1.0 splines_4.2.2 lazyeval_0.2.2
[57] spatstat.geom_3.3-2 reshape2_1.4.4 abind_1.4-5 httpuv_1.6.15
[61] tools_4.2.2 cubature_2.1.1 RColorBrewer_1.1-3 ggdendro_0.2.0
[65] BiocGenerics_0.44.0 ggridges_0.5.6 Rcpp_1.0.13 hash_2.2.6.3
[69] plyr_1.8.9 base64enc_0.1-3 zlibbioc_1.44.0 RCurl_1.98-1.16
[73] deldir_2.0-4 pbapply_1.7-2 cowplot_1.1.3 S4Vectors_0.36.2
[77] zoo_1.8-12 iNEXT_3.0.1 SummarizedExperiment_1.28.0 ggrepel_0.9.5
[81] cluster_2.1.4 magrittr_2.0.3 data.table_1.16.0 RSpectra_0.16-2
[85] scattermore_1.2 SparseM_1.84-2 lmtest_0.9-40 RANN_2.6.2
[89] whisker_0.4.1 truncdist_1.0-2 fitdistrplus_1.2-1 matrixStats_0.61.0
[93] gsl_2.1-8 hms_1.1.3 mime_0.12 xtable_1.8-4
[97] fastDummies_1.7.4 IRanges_2.32.0 gridExtra_2.3 tfruns_1.5.3
[101] compiler_4.2.2 KernSmooth_2.23-20 htmltools_0.5.8.1 later_1.3.2
[105] tzdb_0.4.0 tweenr_2.0.3 MASS_7.3-58.1 Matrix_1.6-4
[109] cli_3.6.3 parallel_4.2.2 dotCall64_1.1-1 evd_2.3-7
[113] igraph_2.0.3 GenomicRanges_1.50.2 pkgconfig_2.0.3 plotly_4.10.4
[117] spatstat.sparse_3.1-0 stringdist_0.9.12 XVector_0.38.0 digest_0.6.37
[121] sctransform_0.4.1 RcppAnnoy_0.0.22 spatstat.data_3.1-2 leiden_0.4.3.1
[125] uwot_0.2.2 evmix_2.12 shiny_1.9.1 quantreg_5.98
[129] rjson_0.2.20 lifecycle_1.0.4 nlme_3.1-160 jsonlite_1.8.8
[133] fansi_1.0.6 pillar_1.9.0 lattice_0.20-45 fastmap_1.2.0
[137] httr_1.4.7 survival_3.4-0 glue_1.7.0 png_0.1-8
[141] ggforce_0.4.2 stringi_1.8.4 RcppHNSW_0.6.0 memoise_2.0.1
[145] irlba_2.3.5.1 future.apply_1.11.2