# How to reanalyze the results of scTensor

# Summary of the output objects of scTensor

Here, we introduced the objects saved in reanalysis.RData.

    library("scTensor")
    load("reanalysis.RData")

After performing `cellCellReport`, some R objects are saved in the reanalysis.RData as follows;

- sce : SingleCellExperiment object
  - metadata(sce)$lrbase : The file pass to the database file of LRBase
  - metadata(sce)$color : The color vector specified by `cellCellSetting`
  - metadata(sce)$label : The label vector specified by `cellCellSetting`
  - metadata(sce)$algorithm : The algorithm for performing scTensor
  - metadata(sce)$sctensor : The results of scTensor
    - metadata(sce)$sctensor$ligand : The factor matrix (Ligand)
    - metadata(sce)$sctensor$receptor : The factor matrix (Receptor)
    - metadata(sce)$sctensor$lrpair : The core tensor
  - metadata(sce)$datasize : The data size of CCI tensor
  - metadata(sce)$ranks : The number of lower dimension in each direction of CCI tensor
  - metadata(sce)$recerror : Reconstruction Error of NTD
  - metadata(sce)$relchange : Relative Change of NTD
- input : The gene expression matrix <# Genes * # Cells>
- twoD : The result of 2D dimensional reduction (e.g. t-SNE)
- LR : The Ligand-Receptor corresponding table extracted from LRBase.XXX.eg.db
- celltypes : The celltype label and color scheme
- index : The core tensor values
- corevalue : The core tensor values (normalized)
- selected : The selected corevalue position with thr threshold “thr”
- ClusterL : The result of analysis in each L vector
- ClusterR : The result of analysis in each R vector
- out.vecLR : The result of analysis in LR pairs
- g : The igraph object to visualize ligand-receptor gene network

# Execution of scTensor with the different options

Using the `reanalysis.RData`, some users may want to perform scTensor with different parameters.

For example, some users want to perform `cellCellDecomp` with different ranks, perform `cellCellReport` with omitting some enrichment analysis, provide the results to their collaborators.

To do such tasks, just type like belows.

    library("AnnotationHub")
    library("LRBaseDbi")

    # Create LRBase object
    ah <- AnnotationHub()
    dbfile <- query(ah, c("LRBaseDb", "Homo sapiens"))[[1]]
    LRBase.Hsa.eg.db <- LRBaseDbi::LRBaseDb(dbfile)

    # Register the file pass of user's LRBase
    metadata(sce)$lrbase <- dbfile(LRBase.Hsa.eg.db)

    # CCI Tensor Decomposition
    cellCellDecomp(sce, ranks=c(6,5), assayNames="normcounts")

    # HTML Report
    cellCellReport(sce, reducedDimNames="TSNE", assayNames="normcounts",
        title="Cell-cell interaction within Germline_Male, GSE86146",
        author="Koki Tsuyuzaki", html.open=TRUE,
        goenrich=TRUE, meshenrich=FALSE, reactomeenrich=FALSE,
        doenrich=FALSE, ncgenrich=FALSE, dgnenrich=FALSE)

# Session information

    ## R version 4.5.2 (2025-10-31)
    ## Platform: x86_64-pc-linux-gnu
    ## Running under: Ubuntu 24.04.4 LTS
    ##
    ## Matrix products: default
    ## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
    ## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
    ##
    ## locale:
    ##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
    ##  [3] LC_TIME=en_US.UTF-8        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: Etc/UTC
    ## tzcode source: system (glibc)
    ##
    ## attached base packages:
    ## [1] stats4    stats     graphics  grDevices utils     datasets  methods
    ## [8] base
    ##
    ## other attached packages:
    ##  [1] scTGIF_1.25.0
    ##  [2] Homo.sapiens_1.3.1
    ##  [3] TxDb.Hsapiens.UCSC.hg19.knownGene_3.22.1
    ##  [4] org.Hs.eg.db_3.22.0
    ##  [5] GO.db_3.22.0
    ##  [6] OrganismDbi_1.53.2
    ##  [7] GenomicFeatures_1.63.1
    ##  [8] AnnotationDbi_1.73.0
    ##  [9] SingleCellExperiment_1.33.1
    ## [10] SummarizedExperiment_1.41.1
    ## [11] Biobase_2.71.0
    ## [12] GenomicRanges_1.63.1
    ## [13] Seqinfo_1.1.0
    ## [14] IRanges_2.45.0
    ## [15] S4Vectors_0.49.0
    ## [16] MatrixGenerics_1.23.0
    ## [17] matrixStats_1.5.0
    ## [18] scTensor_2.21.0
    ## [19] RSQLite_2.4.6
    ## [20] LRBaseDbi_2.21.0
    ## [21] AnnotationHub_4.1.0
    ## [22] BiocFileCache_3.1.0
    ## [23] dbplyr_2.5.2
    ## [24] BiocGenerics_0.57.0
    ## [25] generics_0.1.4
    ## [26] BiocStyle_2.39.0
    ##
    ## loaded via a namespace (and not attached):
    ##   [1] fs_1.6.7                 bitops_1.0-9             enrichplot_1.31.4
    ##   [4] httr_1.4.8               webshot_0.5.5            RColorBrewer_1.1-3
    ##   [7] Rgraphviz_2.55.0         tools_4.5.2              backports_1.5.0
    ##  [10] R6_2.6.1                 lazyeval_0.2.2           withr_3.0.2
    ##  [13] graphite_1.57.0          gridExtra_2.3            schex_1.25.0
    ##  [16] fdrtool_1.2.18           cli_3.6.5                TSP_1.2.6
    ##  [19] scatterpie_0.2.6         entropy_1.3.2            sass_0.4.10
    ##  [22] S7_0.2.1                 genefilter_1.93.0        meshr_2.17.0
    ##  [25] Rsamtools_2.27.1         systemfonts_1.3.2        yulab.utils_0.2.4
    ##  [28] gson_0.1.0               DOSE_4.5.1               MeSHDbi_1.47.0
    ##  [31] AnnotationForge_1.53.0   nnTensor_1.3.0           plotrix_3.8-14
    ##  [34] maps_3.4.3               visNetwork_2.1.4         gridGraphics_0.5-1
    ##  [37] GOstats_2.77.0           BiocIO_1.21.0            dplyr_1.2.0
    ##  [40] dendextend_1.19.1        Matrix_1.7-4             abind_1.4-8
    ##  [43] lifecycle_1.0.5          yaml_2.3.12              SparseArray_1.11.10
    ##  [46] grid_4.5.2               blob_1.3.0               misc3d_0.9-2
    ##  [49] crayon_1.5.3             ggtangle_0.1.1           lattice_0.22-9
    ##  [52] msigdbr_25.1.1           cigarillo_1.1.0          annotate_1.89.0
    ##  [55] KEGGREST_1.51.1          sys_3.4.3                maketools_1.3.2
    ##  [58] pillar_1.11.1            knitr_1.51               tcltk_4.5.2
    ##  [61] rjson_0.2.23             codetools_0.2-20         glue_1.8.0
    ##  [64] ggiraph_0.9.6            outliers_0.15            ggfun_0.2.0
    ##  [67] fontLiberation_0.1.0     data.table_1.18.2.1      vctrs_0.7.1
    ##  [70] png_0.1-8                treeio_1.35.0            spam_2.11-3
    ##  [73] rTensor_1.4.9            gtable_0.3.6             assertthat_0.2.1
    ##  [76] cachem_1.1.0             xfun_0.56                S4Arrays_1.11.1
    ##  [79] tidygraph_1.3.1          survival_3.8-6           seriation_1.5.8
    ##  [82] iterators_1.0.14         fields_17.1              nlme_3.1-168
    ##  [85] Category_2.77.0          ggtree_4.1.1             bit64_4.6.0-1
    ##  [88] fontquiver_0.2.1         filelock_1.0.3           bslib_0.10.0
    ##  [91] otel_0.2.0               DBI_1.3.0                tidyselect_1.2.1
    ##  [94] bit_4.6.0                compiler_4.5.2           curl_7.0.0
    ##  [97] httr2_1.2.2              graph_1.89.1             fontBitstreamVera_0.1.1
    ## [100] DelayedArray_0.37.0      plotly_4.12.0            rtracklayer_1.71.3
    ## [103] checkmate_2.3.4          scales_1.4.0             hexbin_1.28.5
    ## [106] RBGL_1.87.0              plot3D_1.4.2             rappdirs_0.3.4
    ## [109] stringr_1.6.0            digest_0.6.39            rmarkdown_2.30
    ## [112] ca_0.71.1                XVector_0.51.0           htmltools_0.5.9
    ## [115] pkgconfig_2.0.3          fastmap_1.2.0            rlang_1.1.7
    ## [118] htmlwidgets_1.6.4        farver_2.1.2             jquerylib_0.1.4
    ## [121] jsonlite_2.0.0           BiocParallel_1.45.0      GOSemSim_2.37.2
    ## [124] RCurl_1.98-1.17          magrittr_2.0.4           ggplotify_0.1.3
    ## [127] dotCall64_1.2            patchwork_1.3.2          Rcpp_1.1.1
    ## [130] babelgene_22.9           ape_5.8-1                ggnewscale_0.5.2
    ## [133] viridis_0.6.5            gdtools_0.5.0            stringi_1.8.7
    ## [136] tagcloud_0.7.0           ggraph_2.2.2             MASS_7.3-65
    ## [139] plyr_1.8.9               parallel_4.5.2           ggrepel_0.9.7
    ## [142] Biostrings_2.79.5        graphlayouts_1.2.3       splines_4.5.2
    ## [145] igraph_2.2.2             enrichit_0.1.3           buildtools_1.0.0
    ## [148] reshape2_1.4.5           BiocVersion_3.23.1       XML_3.99-0.22
    ## [151] evaluate_1.0.5           BiocManager_1.30.27      foreach_1.5.2
    ## [154] tweenr_2.0.3             tidyr_1.3.2              purrr_1.2.1
    ## [157] polyclip_1.10-7          heatmaply_1.6.0          ggplot2_4.0.2
    ## [160] ReactomePA_1.55.1        ggforce_0.5.0            xtable_1.8-8
    ## [163] restfulr_0.0.16          reactome.db_1.95.0       tidytree_0.4.7
    ## [166] tidydr_0.0.6             viridisLite_0.4.3        tibble_3.3.1
    ## [169] aplot_0.2.9              ccTensor_1.0.3           memoise_2.0.1
    ## [172] registry_0.5-1           GenomicAlignments_1.47.0 cluster_2.1.8.2
    ## [175] concaveman_1.2.0         GSEABase_1.73.0