Configure local cache and hidden environment variables

BulkSignalR donwloads resource files just once after the first installation.

A mecanism handled by BioCFileCache package informs the user if the local files are up to date. Several functions as cacheVersion and cacheInfo give informations about the content of the local cache and its synchronization state with its remote source.

Cache directory can be cleaned by cacheClear function and and forced to be created again using createResources(onRequest=TRUE). Otherwise it will be automatically recreated when the package is next loaded.

The knowledge database (pathways - GO-BP / Reactome, Ligand & recepors - LRdb, and gene Network are handled inside a hidden environment variable called .SignalR)

The sources can be rewritten using resetPathways, resetLRdb and resetNetwork.

Several data versions can be access remotely from : here These datasets can be used to reset the sources locally.

# You can see hidden environment variable list as follows.
ls(BulkSignalR:::.SignalR)

# Setup Pathways for reactome (can be done for GO-BP also)

subset <- c("REACTOME_BASIGIN_INTERACTIONS",
"REACTOME_SYNDECAN_INTERACTIONS",
"REACTOME_ECM_PROTEOGLYCANS",
"REACTOME_CELL_JUNCTION_ORGANIZATION")

reactSubset <- BulkSignalR:::.SignalR$BulkSignalR_Reactome[
BulkSignalR:::.SignalR$BulkSignalR_Reactome$`Reactome name` %in% subset,]

resetPathways(dataframe = reactSubset,
resourceName = "Reactome")

cacheInfo()
cacheVersion()

cacheClear()

# Ask to download again
createResources(onRequest=TRUE)


# Set up LRdb
df <- data.frame(
  ligand    = c("A2M", "AANAT", "AANAT", "ACE", "ACE"),
  receptor  = c("LRP1", "MTNR1A", "MTNR1B", "AGTR2", "BDKRB2")
)
resetLRdb(df,switch=TRUE)

# Set up Network
df <- data.frame(
  a.gn   = c("A2M", "AANAT", "AANAT", "ACE", "ACE"),
  type  = c("regulates-transcription-of",
   "regulates-transcription-of",
   "regulates-transcription-of", 
   "regulates-transcription-of", 
   "regulates-transcription-of"),
  b.gn  = c("LRP1", "MTNR1A", "MTNR1B", "AGTR2", "BDKRB2")
)

resetNetwork(df)

Thank you for reading this guide and for using BulkSignalR.

Session Information

sessionInfo()

## R version 4.5.1 (2025-06-13)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.3 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.22-bioc/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/liblapack.so.3;  LAPACK version 3.12.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              LC_COLLATE=C              
##  [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       
## 
## time zone: America/New_York
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] BulkSignalR_1.1.4
## 
## loaded via a namespace (and not attached):
##   [1] DBI_1.2.3                   bitops_1.0-9               
##   [3] grr_0.9.5                   gridExtra_2.3              
##   [5] httr2_1.2.1                 rlang_1.1.6                
##   [7] magrittr_2.0.3              clue_0.3-66                
##   [9] GetoptLong_1.0.5            matrixStats_1.5.0          
##  [11] compiler_4.5.1              RSQLite_2.4.2              
##  [13] gprofiler2_0.2.3            png_0.1-8                  
##  [15] vctrs_0.6.5                 ggalluvial_0.12.5          
##  [17] pkgconfig_2.0.3             SpatialExperiment_1.19.1   
##  [19] shape_1.4.6.1               crayon_1.5.3               
##  [21] fastmap_1.2.0               backports_1.5.0            
##  [23] dbplyr_2.5.0                magick_2.8.7               
##  [25] XVector_0.49.0              rmarkdown_2.29             
##  [27] purrr_1.1.0                 bit_4.6.0                  
##  [29] xfun_0.52                   glmnet_4.1-10              
##  [31] cachem_1.1.0                aplot_0.2.8                
##  [33] jsonlite_2.0.0              blob_1.2.4                 
##  [35] DelayedArray_0.35.2         broom_1.0.9                
##  [37] parallel_4.5.1              cluster_2.1.8.1            
##  [39] R6_2.6.1                    bslib_0.9.0                
##  [41] RColorBrewer_1.1-3          car_3.1-3                  
##  [43] GenomicRanges_1.61.1        jquerylib_0.1.4            
##  [45] Rcpp_1.1.0                  Seqinfo_0.99.2             
##  [47] SummarizedExperiment_1.39.1 iterators_1.0.14           
##  [49] knitr_1.50                  IRanges_2.43.0             
##  [51] Matrix_1.7-3                splines_4.5.1              
##  [53] igraph_2.1.4                tidyselect_1.2.1           
##  [55] dichromat_2.0-0.1           abind_1.4-8                
##  [57] yaml_2.3.10                 doParallel_1.0.17          
##  [59] codetools_0.2-20            curl_6.4.0                 
##  [61] lattice_0.22-7              tibble_3.3.0               
##  [63] withr_3.0.2                 treeio_1.33.0              
##  [65] Biobase_2.69.0              evaluate_1.0.4             
##  [67] Rtsne_0.17                  gridGraphics_0.5-1         
##  [69] survival_3.8-3              BiocFileCache_2.99.5       
##  [71] circlize_0.4.16             ggtree_3.17.1              
##  [73] pillar_1.11.0               ggpubr_0.6.1               
##  [75] filelock_1.0.3              carData_3.0-5              
##  [77] MatrixGenerics_1.21.0       foreach_1.5.2              
##  [79] stats4_4.5.1                plotly_4.11.0              
##  [81] ggfun_0.2.0                 generics_0.1.4             
##  [83] RCurl_1.98-1.17             S4Vectors_0.47.0           
##  [85] ggplot2_3.5.2               tidytree_0.4.6             
##  [87] scales_1.4.0                glue_1.8.0                 
##  [89] orthogene_1.15.0            lazyeval_0.2.2             
##  [91] tools_4.5.1                 data.table_1.17.8          
##  [93] ggsignif_0.6.4              babelgene_22.9             
##  [95] RANN_2.6.2                  fs_1.6.6                   
##  [97] grid_4.5.1                  ape_5.8-1                  
##  [99] tidyr_1.3.1                 colorspace_2.1-1           
## [101] SingleCellExperiment_1.31.1 patchwork_1.3.1            
## [103] nlme_3.1-168                homologene_1.4.68.19.3.27  
## [105] Formula_1.2-5               cli_3.6.5                  
## [107] rappdirs_0.3.3              viridisLite_0.4.2          
## [109] S4Arrays_1.9.1              ComplexHeatmap_2.25.2      
## [111] dplyr_1.1.4                 gtable_0.3.6               
## [113] stabledist_0.7-2            yulab.utils_0.2.0          
## [115] rstatix_0.7.2               sass_0.4.10                
## [117] digest_0.6.37               BiocGenerics_0.55.1        
## [119] ggplotify_0.1.2             SparseArray_1.9.1          
## [121] ggrepel_0.9.6               htmlwidgets_1.6.4          
## [123] rjson_0.2.23                farver_2.1.2               
## [125] memoise_2.0.1               htmltools_0.5.8.1          
## [127] multtest_2.65.0             lifecycle_1.0.4            
## [129] httr_1.4.7                  GlobalOptions_0.1.2        
## [131] bit64_4.6.0-1               MASS_7.3-65