get_bar_and_dens_class_interactions: Do node neighbor comparison for all taxa within network
In ConesaLab/MDM: Complete MDM Network Analysis for 16S rRNA Data

Description Usage Arguments Value Examples

Find Class neighbors of nodes for all nodes in network and calculate frequency of these interactions (frequency of shared edges). Create bar chart of the frequency of each neighbor interaction. Calculate self-self interactions and create density plots to compare all self-self/all possible interactions vs MDM self-self interactions

1	get_bar_and_dens_class_interactions(orig_graph, orig_phylo, met_type)

`orig_graph`	Graph object of all taxa present in network
`orig_phylo`	Phyloseq object of all taxa in network
`met_type`	Name of environment

Returns List of 4 (list) objects

`barplot_of_interactions_l`	For each unique class node, the frequency of interactions with all neighbors are shown in bar chart format
`pie_b_plot_interactions_l`	For each unique class node, the frequency of interactions with all neighbors are shown in pie chart format
`dens_plot_all_poss2`	Density plots showing all possible class interactions vs MDM self-self interactions
`dens_plot_just_sameclass_poss2`	Density plots showing all self-self class interactions vs MDM self-self interactions

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (orig_graph, orig_phylo, met_type)
{
    edgeDF = as.data.frame(igraph::as_edgelist(orig_graph))
    colnames(edgeDF) = c("X1", "X2")
    edgeDF_w_alltaxnames <- (merge(tax_table(orig_phylo), edgeDF,
        by.x = "row.names", by.y = "X1"))
    edgeDF_w_alltaxnames_updated <- merge(edgeDF_w_alltaxnames,
        tax_table(orig_phylo), by.x = "X2", by.y = "row.names",
        all.x = TRUE)
    print(nrow(edgeDF_w_alltaxnames_updated))
    identical(nrow(edgeDF_w_alltaxnames_updated), nrow(edgeDF))
    colnames(edgeDF_w_alltaxnames_updated)[1:2] = c("Y", "X")
    edgeDF_w_alltaxnames_updated$Class.x <- as.character(edgeDF_w_alltaxnames_updated$Class.x)
    edgeDF_w_alltaxnames_updated$Class.y <- as.character(edgeDF_w_alltaxnames_updated$Class.y)
    edgeDF_w_alltaxnames_updated[is.na(edgeDF_w_alltaxnames_updated$Class.x),
        ]$Class.x = "Unknown"
    edgeDF_w_alltaxnames_updated[is.na(edgeDF_w_alltaxnames_updated$Class.y),
        ]$Class.y = "Unknown"
    edgeDF_w_alltaxnames_updated[edgeDF_w_alltaxnames_updated$Y ==
        "0", ]$Class.y = "Unknown"
    edgeDF_w_alltaxnames_updated$combinedXY = with(edgeDF_w_alltaxnames_updated,
        paste0(Class.x, "&", Class.y))
    barplot_of_interactions_l <- list()
    pie_b_plot_interactions_l <- list()
    for (x_class in unique(edgeDF_w_alltaxnames_updated$Class.x)) {
        edge_df_for_class = as.data.frame(table(edgeDF_w_alltaxnames_updated[grep(x_class,
            edgeDF_w_alltaxnames_updated$combinedXY), ]$combinedXY))
        x_class_at_end = paste0("&", x_class)
        all_to_rep <- edge_df_for_class$Var1[grep(x_class_at_end,
            edge_df_for_class$Var1)]
        test_st <- strsplit(as.character(all_to_rep), "&")
        test_st2 <- lapply(test_st, function(x) {
            new_var <- paste0(x_class, "&", x[1])
            return(new_var)
        })
        edge_df_for_class$Var1 <- as.character(edge_df_for_class$Var1)
        edge_df_for_class$Var1[all_to_rep] = (unlist(test_st2))
        edge_df_for_class <- edge_df_for_class %>% mutate(size = Freq/sum(Freq))
        same_class_var = paste0(x_class, "&", x_class)
        edge_df_for_class$Var1 <- as.factor(edge_df_for_class$Var1)
        b_plot <- ggplot(edge_df_for_class, aes(Var1, Freq, fill = Var1)) +
            geom_bar(stat = "identity")
        b_plot <- b_plot + geom_bar(stat = "identity", data = edge_df_for_class[edge_df_for_class$Var1 %in%
            same_class_var, ], aes(Var1), size = 1, fill = "grey50",
            color = "black") + coord_flip() + theme(legend.position = "none",
            axis.title.y = element_blank())
        b_plot <- b_plot + ggtitle(paste("Neighbor Interactions for Class ",
            x_class, sep = " "))
        custom_colors = rainbow(length(unique(edge_df_for_class$Var1)))
        num_to_change_to_grey = which(levels(edge_df_for_class$Var1) ==
            same_class_var)
        custom_colors[num_to_change_to_grey] = "grey50"
        pie_b_plot <- ggplot(edge_df_for_class, aes(x = "", y = size,
            fill = Var1)) + geom_bar(width = 1, stat = "identity",
            position = position_fill()) + scale_fill_manual(values = custom_colors) +
            coord_polar("y", start = 0) + geom_text(aes(label = paste0(round(size *
            100), "%")), position = position_fill(vjust = 0.6),
            size = 3) + theme(axis.title.y = element_blank(),
            axis.title.x = element_blank(), panel.border = element_blank(),
            panel.grid = element_blank(), panel.background = element_blank(),
            axis.ticks = element_blank(), axis.text.x = element_blank()) +
            theme(legend.text = element_text(size = 7)) + guides(color = guide_legend(override.aes = list(size = 1)))
        barplot_of_interactions_l[[x_class]] = b_plot
        pie_b_plot_interactions_l[[x_class]] = pie_b_plot
    }
    combinedXY_df = as.data.frame(table(edgeDF_w_alltaxnames_updated$combinedXY))
    val_of_unk1 = combinedXY_df[which(combinedXY_df$Var1 == "Unknown&Unknown"),
        ]$Freq
    next_smallest_val1 = val_of_unk1 - 1
    p_val_sig_dif = length(which(combinedXY_df$Freq > next_smallest_val1))/length(combinedXY_df$Freq)
    p_val_sig_dif = round(p_val_sig_dif, digits = 5)
    d <- density(combinedXY_df$Freq)
    y_axis_max_dens <- max(d$y)
    dens_plot_all_poss <- ggplot(combinedXY_df, aes(Freq)) +
        geom_density() + geom_vline(xintercept = val_of_unk1,
        linetype = "dashed", color = "red", size = 1) + ggtitle(paste(met_type,
        "All Possible Interactions", sep = " "))
    dens_plot_all_poss2 <- dens_plot_all_poss + geom_label(aes(x = val_of_unk1,
        y = y_axis_max_dens, label = paste("P-value =", p_val_sig_dif,
            sep = " ")), color = "black", angle = 0, hjust = "inward")
    dens_plot_all_poss2 <- dens_plot_all_poss2 + geom_label(aes(x = val_of_unk1,
        y = y_axis_max_dens/2, label = paste("Unknown-Unknown"),
        hjust = "inward"))
    print(dens_plot_all_poss2)
    combinedXY_just_sameclass_df = as.data.frame(table(edgeDF_w_alltaxnames_updated[edgeDF_w_alltaxnames_updated$Class.x ==
        edgeDF_w_alltaxnames_updated$Class.y, ]$combinedXY))
    val_of_unk2 = combinedXY_just_sameclass_df[which(combinedXY_just_sameclass_df$Var1 ==
        "Unknown&Unknown"), ]$Freq
    next_smallest_val2 = val_of_unk2 - 1
    p_val_sig_dif2 = length(which(combinedXY_just_sameclass_df$Freq >
        next_smallest_val2))/length(combinedXY_just_sameclass_df$Freq)
    p_val_sig_dif2 = round(p_val_sig_dif2, digits = 5)
    d2 <- density(combinedXY_just_sameclass_df$Freq)
    y_axis_max_dens2 <- max(d2$y)
    dens_plot_just_sameclass_poss <- ggplot(combinedXY_just_sameclass_df,
        aes(Freq)) + geom_density() + geom_vline(xintercept = val_of_unk2,
        linetype = "dashed", color = "red", size = 1) + ggtitle(paste(met_type,
        "Self-self Class Interactions", sep = " "))
    dens_plot_just_sameclass_poss2 <- dens_plot_just_sameclass_poss +
        geom_label(aes(x = val_of_unk2, y = y_axis_max_dens2,
            label = paste("P-value =", p_val_sig_dif2, sep = " ")),
            color = "black", angle = 0, hjust = "inward")
    dens_plot_just_sameclass_poss2 <- dens_plot_just_sameclass_poss2 +
        geom_label(aes(x = val_of_unk2, y = y_axis_max_dens2/2,
            label = paste("Unknown-Unknown"), hjust = "inward"))
    print(dens_plot_just_sameclass_poss2)
    bar_pie_and_dens_plots_l <- list(barplot_of_interactions_l,
        pie_b_plot_interactions_l, dens_plot_all_poss2, dens_plot_just_sameclass_poss2)
    return(bar_pie_and_dens_plots_l)
  }