R/methods-plotCountDensity.R

In roryk/bcbioRnaseq: RNA-Seq Utilities

#' Plot Count Density
#'
#' @name plotCountDensity
#' @family Quality Control Functions
#' @author Michael Steinbaugh, Rory Kirchner, Victor Barrera
#'
#' @inheritParams general
#' @param style Desired plot style ("`line`" or "`solid`").
#'
#' @return `ggplot`.
#'
#' @examples
#' # bcbioRNASeq ====
#' plotCountDensity(bcb_small)
#' plotCountDensity(
#'     object = bcb_small,
#'     style = "line",
#'     interestingGroups = "sampleName"
#' )
NULL



# Methods ======================================================================
#' @rdname plotCountDensity
#' @export
setMethod(
    "plotCountDensity",
    signature("bcbioRNASeq"),
    function(
        object,
        interestingGroups,
        normalized = c("tmm", "rlog", "vst", "tpm", "rle"),
        style = c("line", "solid"),
        color = scale_color_hue(),
        fill = scale_fill_hue(),
        title = "count density"
    ) {
        validObject(object)
        if (missing(interestingGroups)) {
            interestingGroups <- bcbioBase::interestingGroups(object)
        }
        normalized <- match.arg(normalized)
        style <- match.arg(style)
        assertIsColorScaleDiscreteOrNULL(color)
        assertIsFillScaleDiscreteOrNULL(fill)
        assertIsAStringOrNULL(title)

        styleLab <- paste(interestingGroups, collapse = ":\n")

        # Subset the counts matrix to only include non-zero genes
        nonzero <- .nonzeroGenes(object)
        counts <- counts(object, normalized = normalized)
        counts <- counts[nonzero, , drop = FALSE]

        # Apply log2 transformation, if  necessary
        if (normalized %in% c("rlog", "vst")) {
            # Already log2
            fxn <- .meltCounts
        } else {
            fxn <- .meltLog2Counts
        }

        # Melt the counts into long format
        data <- fxn(counts, sampleData = sampleData(object))

        # Subtitle
        if (is_a_string(title)) {
            subtitle <- paste(nrow(counts), "non-zero genes")
        } else {
            subtitle <- NULL
        }

        p <- ggplot(
            data = data,
            mapping = aes_string(
                x = "counts",
                group = "interestingGroups",
                color = "interestingGroups",
                fill = "interestingGroups"
            )
        ) +
            labs(
                title = title,
                subtitle = subtitle,
                x = paste(normalized, "counts (log2)"),
                color = styleLab,
                fill = styleLab
            )

        if (style == "line") {
            p <- p + geom_density(fill = NA)
            if (is(color, "ScaleDiscrete")) {
                p <- p + color
            }
        } else if (style == "solid") {
            p <- p + geom_density(alpha = 0.75, color = NA)
            if (is(fill, "ScaleDiscrete")) {
                p <- p + fill
            }
        }

        if (identical(interestingGroups, "sampleName")) {
            p <- p + guides(fill = FALSE)
        }

        p
    }
)