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romanhaa / cerebroApp

R package containing the Cerebro application.
https://romanhaa.github.io/cerebroApp/
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Unable to load example .crb files in v1.3 #19

Closed alexjacobsCDS closed 4 years ago

alexjacobsCDS commented 4 years ago

I am attempting to load the example .crb files provided in the Cerebro repo and getting an error

2020-10-26 16:24:15] Active tab: loadData
[2020-10-26 16:24:24] File to load: /var/folders/f4/g3fts2nd6dngs42nn5b00ppc0000gn/T//RtmpI20lgG/6780fae42d6f64fe913255e4/0.crb
Warning: Error in message: attempt to apply non-function
  [No stack trace available]
Warning: Error in message: attempt to apply non-function
  74: <Anonymous>
Warning: Error in message: attempt to apply non-function
  108: <Anonymous>
Warning: Error in message: attempt to apply non-function
  74: <Anonymous>
Warning: Error in message: attempt to apply non-function
  104: <Anonymous>
Warning: Error in message: attempt to apply non-function
  104: <Anonymous>
Warning: Error in message: attempt to apply non-function
  104: <Anonymous>
Warning: Error in message: attempt to apply non-function
  104: <Anonymous>
Warning: Error in message: attempt to apply non-function
  113: <Anonymous>
Warning: Error in message: attempt to apply non-function
  113: <Anonymous>
Warning: Error in message: attempt to apply non-function
  112: <Anonymous>
Warning: Error in message: attempt to apply non-function
  113: <Anonymous>
Warning: Error in message: attempt to apply non-function
  113: <Anonymous>
Warning: Error in message: attempt to apply non-function
  113: <Anonymous>

This works however if I used v1.2

My session info:

> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.5

Matrix products: default
BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib

Random number generation:
 RNG:     Mersenne-Twister 
 Normal:  Inversion 
 Sample:  Rounding 

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] shiny_1.5.0         cerebroApp_1.3.0    BiocManager_1.30.10

loaded via a namespace (and not attached):
  [1] backports_1.1.10      BiocFileCache_1.10.2  plyr_1.8.6            igraph_1.2.6          lazyeval_0.2.2       
  [6] GSEABase_1.48.0       shinydashboard_0.7.1  splines_3.6.1         crosstalk_1.1.0.1     listenv_0.8.0        
 [11] ggplot2_3.3.2         digest_0.6.27         htmltools_0.5.0       formattable_0.2.0.1   viridis_0.5.1        
 [16] fansi_0.4.1           magrittr_1.5          memoise_1.1.0         tensor_1.5            cluster_2.1.0        
 [21] ROCR_1.0-11           remotes_2.2.0         shinyFiles_0.8.0      globals_0.13.1        readr_1.4.0          
 [26] annotate_1.64.0       matrixStats_0.57.0    askpass_1.1           prettyunits_1.1.1     colorspace_1.4-1     
 [31] blob_1.2.1            rappdirs_0.3.1        ggrepel_0.8.2         xfun_0.18             dplyr_1.0.2          
 [36] callr_3.5.1           crayon_1.3.4          RCurl_1.98-1.2        jsonlite_1.7.1        graph_1.64.0         
 [41] spatstat.data_1.4-3   spatstat_1.64-1       zoo_1.8-8             survival_3.2-7        ape_5.4-1            
 [46] glue_1.4.2            polyclip_1.10-0       gtable_0.3.0          leiden_0.3.3          pkgbuild_1.1.0       
 [51] future.apply_1.6.0    BiocGenerics_0.32.0   abind_1.4-5           scales_1.1.1          msigdbr_7.2.1        
 [56] DBI_1.1.0             miniUI_0.1.1.1        Rcpp_1.0.5            viridisLite_0.3.0     xtable_1.8-4         
 [61] progress_1.2.2        tidytree_0.3.3        reticulate_1.18       rsvd_1.0.3            bit_4.0.4            
 [66] stats4_3.6.1          GSVA_1.34.0           DT_0.16               htmlwidgets_1.5.2     httr_1.4.2           
 [71] RColorBrewer_1.1-2    ellipsis_0.3.1        Seurat_3.2.2          ica_1.0-2             farver_2.0.3         
 [76] pkgconfig_2.0.3       XML_3.99-0.3          uwot_0.1.8            deldir_0.1-29         dbplyr_1.4.4         
 [81] labeling_0.4.2        tidyselect_1.1.0      rlang_0.4.8           reshape2_1.4.4        later_1.1.0.1        
 [86] AnnotationDbi_1.48.0  munsell_0.5.0         tools_3.6.1           cli_2.1.0             generics_0.0.2       
 [91] RSQLite_2.2.1         ggridges_0.5.2        evaluate_0.14         stringr_1.4.0         fastmap_1.0.1        
 [96] goftest_1.2-2         yaml_2.2.1            ggtree_2.0.4          knitr_1.30            processx_3.4.4       
[101] bit64_4.0.5           fs_1.5.0              fitdistrplus_1.1-1    shinycssloaders_1.0.0 purrr_0.3.4          
[106] RANN_2.6.1            pbapply_1.4-3         future_1.19.1         nlme_3.1-150          mime_0.9             
[111] biomaRt_2.42.1        compiler_3.6.1        shinythemes_1.1.2     rstudioapi_0.11       png_0.1-7            
[116] plotly_4.9.2.1        curl_4.3              spatstat.utils_1.17-0 treeio_1.10.0         tibble_3.0.4         
[121] geneplotter_1.64.0    stringi_1.5.3         ps_1.4.0              lattice_0.20-41       Matrix_1.2-18        
[126] shinyjs_2.0.0         vctrs_0.3.4           pillar_1.4.6          lifecycle_0.2.0       lmtest_0.9-38        
[131] RcppAnnoy_0.0.16      data.table_1.13.2     cowplot_1.1.0         bitops_1.0-6          irlba_2.3.3          
[136] patchwork_1.0.1       httpuv_1.5.4          qvalue_2.18.0         R6_2.4.1              promises_1.1.1       
[141] KernSmooth_2.23-17    gridExtra_2.3         IRanges_2.20.2        codetools_0.2-16      colourpicker_1.1.0   
[146] MASS_7.3-53           assertthat_0.2.1      openssl_1.4.3         rprojroot_1.3-2       shinyWidgets_0.5.4   
[151] withr_2.3.0           sctransform_0.3.1     S4Vectors_0.24.4      mgcv_1.8-33           parallel_3.6.1       
[156] hms_0.5.3             rpart_4.1-15          grid_3.6.1            tidyr_1.1.2           rmarkdown_2.5        
[161] rvcheck_0.1.8         Rtsne_0.15            Biobase_2.46.0

Additionally, I'm wondering if I should be able to load an object directly after processing with Seurat, or if I need to pre-process into a cerebro object

Thank you!

romanhaa commented 4 years ago

Hi @alexjacobsCDS!

Unfortunately, I haven't found time yet to process the example data sets in the Cerebro repository with cerebroApp v1.3. Therefore, it is expected that they don't work with Cerebro v1.3. Moreover, due to reasons explained in the release notes of v1.3, I currently can't produce a standalone version of Cerebro v1.3.

Regarding your second question: Data must be exported with cerebroApp functions before loading it into Cerebro. This can be done either from a Seurat file or a SingleCellExperiment file, as explained in the vignettes on the cerebroApp website.

Best, Roman

alexjacobsCDS commented 4 years ago

@romanhaa Thank you for your response! Closing this issue