R/alpha_div_boxplot.R

In compbiomed/animalcules: Interactive microbiome analysis toolkit

#' Alpha diversity boxplot
#'
#' @param MAE A multi-assay experiment object. Required.
#' @param tax_level The taxon level used for organisms. Required.
#' @param condition Which condition to group samples. Required.
#' @param alpha_metric Which alpha diversity metric to use. Required. Can be one
#' of:"inverse_simpson", "gini_simpson", "shannon", "fisher", "coverage", "unit"
#' @return A plotly object
#'
#' @examples
#' data_dir <- system.file("extdata/MAE.rds", package = "animalcules")
#' toy_data <- readRDS(data_dir)
#' p <- alpha_div_boxplot(toy_data,
#'   tax_level = "genus",
#'   condition = "DISEASE",
#'   alpha_metric = "shannon"
#' )
#' p
#'
#' @import dplyr
#' @import plotly
#' @importFrom ggplot2 ggplot aes geom_point geom_boxplot labs
#' @importFrom stats model.matrix quantile t.test wilcox.test
#' @import magrittr
#' @import reshape2
#' @import MultiAssayExperiment
#' @import SummarizedExperiment
#' @export

alpha_div_boxplot <- function(MAE,
    tax_level,
    condition,
    alpha_metric = c(
        "inverse_simpson",
        "gini_simpson", "shannon", "fisher", "coverage", "unit"
    )) {
    # Extract data
    microbe <- MAE[["MicrobeGenetics"]] # double bracket subsetting is easier
    # host <- MAE[['HostGenetics']] organism x taxlev
    tax_table <- as.data.frame(SummarizedExperiment::rowData(microbe))
    # sample x condition
    sam_table <- as.data.frame(SummarizedExperiment::colData(microbe))
    counts_table <- as.data.frame(SummarizedExperiment::assays(microbe))[
        ,
        rownames(sam_table)
    ] # organism x sample
    
    # Sum counts by taxon level and return counts
    counts_table %<>% upsample_counts(tax_table, tax_level)
    
    # calculate alpha diversity
    sam_table$richness <- diversities(counts_table, index = alpha_metric)
    colnames(sam_table)[ncol(sam_table)] <- "richness"
    colnames(sam_table)[which(colnames(sam_table) == condition)] <- "condition"
    
    
    # check if categorical variable
    if (!is.character(sam_table$condition)) {
        # plot alpha diversity boxplot
        g <- ggplot2::ggplot(sam_table, ggplot2::aes(condition,
            .data$richness,
            text = rownames(sam_table),
            color = condition
        )) +
            ggplot2::geom_point() +
            ggplot2::labs(title = paste("Alpha diversity between ",
                condition, " (", alpha_metric, ")",
                sep = ""
            ))
    } else {
        # plot alpha diversity boxplot
        g <- ggplot2::ggplot(sam_table, ggplot2::aes(condition,
            .data$richness,
            text = rownames(sam_table),
            color = condition
        )) +
            ggplot2::geom_point() +
            ggplot2::geom_boxplot() +
            ggplot2::labs(title = paste("Alpha diversity between ",
                condition, " (",
                alpha_metric, ")",
                sep = ""
            ))
    }
    
    # change y title
    g <- g + labs(y = alpha_metric)
    
    g <- ggplotly(g, tooltip = "text")
    g$elementId <- NULL # To suppress a shiny warning
    return(g)
}