R/graph_combination.R

In DrDimont: Drug Response Prediction from Differential Multi-Omics Networks

inter_layer_edgelist_by_id <- function(annotation_A, annotation_B, connection, weight = 1) {
    #' @title [INTERNAL] Inter layer connections by identifiers
    #'
    #' @description [INTERNAL] Returns an edge list defining the connections between two layers of the network.
    #'
    #' @param annotation_A,annotation_B [data.frame] Annotation tables specifying the identifiers of
    #' the nodes of a network
    #' @param connection [string] String of identifier to connect on
    #' @param weight [int|vector] Integer or vector specifying the weight of the inter-layer connections.
    #' 
    #' @return Data frame with columns from, to and weight
    #' @importFrom rlang .data
    #' 
    #' @keywords internal
    #' @export

    inter_graph <- annotation_A %>%
        dplyr::inner_join(annotation_B, by = connection) %>%
        dplyr::select(from=.data$node_id.x, to=.data$node_id.y) %>%
        tibble::add_column(weight = weight)

    return(inter_graph)
}

inter_layer_edgelist_by_table <- function(annotation_A,
                                          annotation_B,
                                          interaction_table,
                                          weight_column) {
    #' @title [INTERNAL] Interaction table to iGraph graph object
    #'
    #' @description [INTERNAL] Returns an edge list defining the connections between two layers of the network
    #' based on an
    #' interaction table supplied by the user.
    #'
    #' @param annotation_A,annotation_B [data.frame] Annotation tables specifying the identifiers of
    #' the nodes of a network
    #' @param interaction_table [data.frame] Table specifying the interaction / connections between the two layers
    #' @param weight_column [string] Name of the column in 'interaction_table' giving the weight of the
    #' inter-layer edges.
    #' 
    #' @return Data frame with columns from, to and weight
    #' @importFrom rlang .data
    #' 
    #' @keywords internal
    #' @export

    id.x <- intersect(colnames(annotation_A), colnames(interaction_table))[1]
    id.y <- intersect(colnames(annotation_B), colnames(interaction_table))[1]

    inter_graph <- annotation_A %>%
        dplyr::inner_join(interaction_table, by = id.x) %>%
        dplyr::inner_join(annotation_B, by = id.y) %>%
        dplyr::rename(weight = dplyr::all_of(weight_column)) %>%
        dplyr::select(from=.data$node_id.x, to=.data$node_id.y, .data$weight)

    return(inter_graph)
}

combine_graphs <- function(graphs, inter_layer_edgelists) {
    #' @title [INTERNAL] Combine graphs by adding inter-layer edges
    #'
    #' @description [INTERNAL] Creates the union of all graphs and adds the inter-layer edges.
    #'
    #' @param graphs [list] List of iGraph objects
    #' @param inter_layer_edgelists [list] List of data frames containing inter-layer edges
    #'
    #' @return iGraph object which is the union of the input graphs with isolated nodes removed.
    #' 
    #' @keywords internal
    #' @export

    all_inter_layer_edges <- dplyr::bind_rows(inter_layer_edgelists)
    inter_layer_edges <- as.vector(t(as.matrix(all_inter_layer_edges[ , 1:2])))
    inter_layer_weights <- as.vector(all_inter_layer_edges[ , 3])

    union <- igraph::disjoint_union(graphs)
    union <- igraph::add_edges(graph = union,
                                edges = inter_layer_edges,
                                weight = inter_layer_weights)
    return(union)
}