Code

    library(BulkSignalR)

## 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.

Code

    # 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

Code

    sessionInfo()

    ## R version 4.5.1 (2025-06-13 ucrt)
    ## Platform: x86_64-w64-mingw32/x64
    ## Running under: Windows Server 2022 x64 (build 20348)
    ##
    ## Matrix products: default
    ##   LAPACK version 3.12.1
    ##
    ## locale:
    ## [1] LC_COLLATE=C
    ## [2] LC_CTYPE=English_United States.utf8
    ## [3] LC_MONETARY=English_United States.utf8
    ## [4] LC_NUMERIC=C
    ## [5] LC_TIME=English_United States.utf8
    ##
    ## time zone: America/New_York
    ## tzcode source: internal
    ##
    ## 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