annotateGO              Perform GO annotation of input data
annotatePathways        Annotate pathways for input data
buildPairsbyFunctionMatrix
                        Build binary matrix with int-pairs in rows,
                        functions in cols
checkLL_RR              Manually change the annotation of L-L and R-R
                        pairs
circlePlot              Plot circle plot
combineAnnotations      Combine GO annotation and pathways in a unique
                        object
createBarPlot1_ggplot   Create ggplot barplot to be saved in tiff
createBarPlot2_CV       Create barplot of number of interaction for
                        selected cluster
createBarPlot2_ggplot   Create ggplot barplot of Nint per cluster
                        selected
createBarPlot_CV        Create Barplot cluster-verse
createNetwork           Create Network of clusters
dendroIntPairModules    Get dendrogram of int pair modules
elbowPoint              Determine the elbow point on a curve (from
                        package akmedoids)
ensemblLink             Get html link to ensembl
getBack2BackBarplot     Get back-to-back barplot for 2 conditions
                        comparison
getBarplotDF            Get dataframe for plotting barplot (all
                        clusters)
getBarplotDF2           Get dataframe for barplot (by cluster)
getClusterA_Names       Get cluster names only from sender cluster A
getClusterColors        Get colors for clusters
getClusterNames         Get clusters names from initial input data
getClusterNetwork       Creating edges dataframe for network of
                        clusters
getClusterSize          Get Clusters size
getDistinctCouplets     Get table of unique int-pairs/clust-pairs
                        couplets
getDotPlot_selInt       Functions to plot DotPlots
getGObiomaRt            Connection to Ensembl via biomaRt to get GO
                        terms
getGeneTable            Get table for gene-verse
getHitsf                Subfunction to calculate significant functions
                        by permutation test
getIntFlow              Get subset of interactions corresponding to a
                        certain viewpoint and flow
getNtermsBYdb           Calculate number of terms of a database
getNumLR                Get number of unique ligands and receptors
getPieChart             Get Pie Chart of unique couplets
getRadar_df             #' Get radar plot of relative numbers of
                        interactions for a certain cell type #' #'
                        @param tab_c1 barplot dataframe from Viewpoint
                        generated by getBarplotDF2() containing data
                        for condition 1 #' @param tab_c2 barplot
                        dataframe from Viewpoint generated by
                        getBarplotDF2() containing data for condition 2
                        #' @param tab_c3 barplot dataframe from
                        Viewpoint generated by getBarplotDF2()
                        containing data for condition 3 #' @param
                        lab_c1 label for condition 1 #' @param lab_c2
                        label for condition 2 #' @param lab_c3 label
                        for condition 3 #' @param cell_name label of
                        cell type of interest #' #' @return plot #'
                        @importFrom fmsb radarchart #' @importFrom
                        data.table transpose getRadarPlot <-
                        function(tab_c1, tab_c2, tab_c3, lab_c1,
                        lab_c2, lab_c3, cell_name) if(is.null(tab_c3))
                        df <- merge(tab_c1, tab_c2, by = "Clusters",
                        all = TRUE) colnames(df) <- c("Clusters",
                        "nint_c1", "nint_c2") else df <- merge(tab_c1,
                        tab_c2, by = "Clusters", all = TRUE) df <-
                        merge(df, tab_c3, by = "Clusters", all = TRUE)
                        colnames(df) <- c("Clusters", "nint_c1",
                        "nint_c2", "nint_c3") df[is.na(df)] <- 0
                        cluster_names <- df$Clusters # add max and min
                        max_nint <- max(df[, -1]) df <- add_column(df,
                        max_nint, .after = "Clusters") df <-
                        add_column(df, "min_nint" = 0, .after =
                        "max_nint") radar_df <-
                        data.table::transpose(df[, -1])
                        if(is.null(lab_c3)) rownames(radar_df) <-
                        c("max", "min", lab_c1, lab_c2) else
                        rownames(radar_df) <- c("max", "min", lab_c1,
                        lab_c2, lab_c3) colnames(radar_df) <-
                        cluster_names color <- c("#438ECC", "#E97778",
                        "#00BA38") fmsb::radarchart( radar_df, axistype
                        = 1, # Customize the polygon pcol = color,
                        pfcol = scales::alpha(color, 0.5), plwd = 2,
                        plty = 1, # Customize the grid cglcol = "grey",
                        cglty = 1, cglwd = 0.8, # Customize the axis
                        axislabcol = "grey30", # Variable labels vlcex
                        = 1.2, vlabels = colnames(radar_df),
                        caxislabels = round(seq(from = 0, to =
                        radar_df["max",1], length.out = 5)), title =
                        cell_name ) legend( x = "bottomleft", legend =
                        rownames(radar_df[-c(1,2),]), horiz = FALSE,
                        bty = "n", pch = 20 , col = color, text.col =
                        "black", cex = 1, pt.cex = 1.5 ) Get radar df
                        of relative numbers of interactions for a
                        certain cell type
getRankedTerms          Get table with ranked functional terms
getSignif_table         Wrapper for other functions to get significant
                        table of func terms
getSignificantFunctions
                        Calculate significant function per intpair
                        module
getSignificantFunctions_multiCond
                        Get significance of functional terms related to
                        unique int-pairs per condition
getSunburst             Get Sunburst plot of selected functional terms
getUMAPipModules        Get UMAP for IP modules
getUniqueDotplot        Plot dotplot containing only unique
                        int-pair/cluster pairs with many conditions
getUniqueIntpairs_byCond
                        Get table of unique int-pairs by condition
goLink                  Get GO link
input.data              Input Data example
read.CPDBv2             Read output from CellPhoneDB v2.
read.SCsignalR          Read output from SingleCellSignalR
read.cellchat           Read dataframe of cell-cell communication from
                        CellChat (ligand/receptor)
read.customInput        Read custom input file and re-structure it with
                        InterCellar format
read.icellnet           Read ICELLNET dataframe
run_app                 Run the Shiny Application
subsetAnnot_multiCond   Subset int-pair by function matrices to unique
                        int-pairs by condition
subsetFuncMatBYFlow     Subset pairs-function matrix by selected flow
swap.RLint              Swaps interaction pairs that are R-L to L-R
uniprotLink             Get html link to uniprot
updateInputLR           Function that orders all interaction pairs as
                        L-R. Leaves unchanged the R-R and L-L
