hemberg-lab
could not find function "calculate_distance"
Hi,
I am trying to use SC3 but running into the following error repeatedly. Please help to resolve this.
sce <- readRDS("data/deng/deng-sce.rds") sce <- sc3(sce, ks = 10, biology = TRUE, n_cores = 1) Setting SC3 parameters... Calculating distances between the cells... starting worker pid=41321 on localhost:11646 at 20:55:46.804 Loading required package: SC3 Loading required package: foreach Loading required package: rngtools Error in calculate_distance(dataset, i) : could not find function "calculate_distance" In addition: Warning message: In library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, : there is no package called ‘SC3’ Error in calculate_distance(dataset, i) : could not find function "calculate_distance" Error in calculate_distance(dataset, i) : could not find function "calculate_distance" Error in checkForRemoteErrors(val) : 3 nodes produced errors; first error: Error in calculate_distance(dataset, i) : could not find function "calculate_distance"
Here is the session info:
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/LAPACK: /general/sw/eb/sw/FlexiBLAS/3.0.4-GCC-11.2.0/lib64/libflexiblas.so.3.0
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
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] SC3_1.26.0
loaded via a namespace (and not attached): [1] Rcpp_1.0.8.3 mvtnorm_1.1-3 [3] lattice_0.20-45 class_7.3-20 [5] assertthat_0.2.1 digest_0.6.29 [7] foreach_1.5.2 SingleCellExperiment_1.20.0 [9] utf8_1.2.2 mime_0.12 [11] R6_2.5.1 GenomeInfoDb_1.34.2 [13] WriteXLS_6.4.0 stats4_4.2.0 [15] pcaPP_1.9-74 e1071_1.7-9 [17] ggplot2_3.3.5 pillar_1.7.0 [19] zlibbioc_1.44.0 rlang_1.0.2 [21] S4Vectors_0.36.0 Matrix_1.5-1 [23] pheatmap_1.0.12 RCurl_1.98-1.6 [25] munsell_0.5.0 proxy_0.4-26 [27] shiny_1.7.1 DelayedArray_0.24.0 [29] httpuv_1.6.5 compiler_4.2.0 [31] pkgconfig_2.0.3 BiocGenerics_0.44.0 [33] htmltools_0.5.2 tidyselect_1.1.2 [35] SummarizedExperiment_1.28.0 tibble_3.1.6 [37] GenomeInfoDbData_1.2.9 IRanges_2.32.0 [39] codetools_0.2-18 matrixStats_0.62.0 [41] fansi_1.0.3 later_1.3.0 [43] crayon_1.5.1 rrcov_1.7-0 [45] dplyr_1.0.8 bitops_1.0-7 [47] grid_4.2.0 xtable_1.8-4 [49] gtable_0.3.0 lifecycle_1.0.1 [51] DBI_1.1.2 magrittr_2.0.3 [53] scales_1.2.0 cli_3.3.0 [55] XVector_0.38.0 ROCR_1.0-11 [57] promises_1.2.0.1 doRNG_1.8.2 [59] doParallel_1.0.17 robustbase_0.95-0 [61] ellipsis_0.3.2 generics_0.1.2 [63] vctrs_0.4.1 RColorBrewer_1.1-3 [65] iterators_1.0.14 tools_4.2.0 [67] Biobase_2.58.0 glue_1.6.2 [69] DEoptimR_1.0-11 purrr_0.3.4 [71] MatrixGenerics_1.10.0 rngtools_1.5.2 [73] fastmap_1.1.0 parallel_4.2.0 [75] colorspace_2.0-3 cluster_2.1.3 [77] GenomicRanges_1.50.1
I
Hello,
and thanks for the question. Unfortunately, the main developer of SC3 has left academia, so there is no longer anyone around with the required technical expertise to resolve this problem. Also, we recently released an upgrade of SC3, https://github.com/hemberg-lab/sc3s, which we believe is superior to the original version. The only potential downside is that the new version is implemented in python instead of R.
Sorry for not being able to provide better assistance here.
