R/Plot.deg.R

In DEComplexDisease: A tool for differential expression analysis and DEGs based investigation to complex diseases by bi-clustering analysis

#' Plot the DEGs before or after cross-validation
#'
#' Plot the binary differential expression matrix transformed by \code{\link{bi.deg}}
#'
#' @import ComplexHeatmap
#' @import grid
#' @importFrom grDevices rainbow
#' @importFrom graphics abline axis legend lines mtext par plot points points text
#' @param input a 'deg' object returned by \code{\link{bi.deg}}
#' @param ann a data.frame for the patient annotation
#' @param col.order the order of column in heatmap
#' @param show.genes the gene ids to plot
#' @param max.n the maximum number of genes to plot
#' @param up.col the color for up-regulated genes
#' @param down.col the color for down-regulated genes
#' @param ... other setting of 'oncoPrint'
#'
#' @author Guofeng Meng
#'
#'
#' @details This function applied the function of oncoPrint from `ComplexHeatmap` to dispaly ownership of the DEGs. The output is a heatmap plots where the genes with maximum observations are showed.
#'
#' @return A heatmap plot
#'
#' @examples
#' Plot(deg,ann.er, max.n=5)
#' Plot(deg.spc, ann.er, max.n=5)
#'
#' @export

Plot.deg <- function(input, ann = NULL, col.order = NULL, show.genes = NULL, max.n = 30,
    up.col = "red", down.col = "blue", ...) {
    if (!is.null(ann) & !is(ann, "data.frame"))
        stop("Error: ann: should be data.frame!")
    input = as.matrix(input)
    ges = row.names(input)
    pas = colnames(input)
    if (!all(unique(as.vector(input)) %in% c(1, -1, 0)))
        stop("Error: deg: valid values are  1, -1 and 0")
    if (is.null(show.genes)) {
        aa = sort(apply(input, 1, function(x) length(x[x != 0])), decreasing = TRUE)
        show.genes = names(aa[seq_len(min(max.n, dim(input)[1]))])
        if (aa[length(show.genes)] == 0)
            show.genes = names(aa[aa != 0])
    } else {
        all.ids = row.names(input)
        show.genes = show.genes[show.genes %in% all.ids]
    }
    if (length(show.genes) == 0)
        stop("Error: show.genes: cannot recognize the ids")
    mat.deg = t(vapply(show.genes, function(x) {
        y = input[x, ]
        rr = rep("", length(y))
        rr[y == 1] = "Up"
        rr[y == -1] = "Down"
        return(rr)
    }, rep("Up", ncol(input))))


    row.names(mat.deg) <- show.genes
    colnames(mat.deg) <- colnames(input)

    ha = NULL
    if (!is.null(ann)) {
        has.pas = row.names(ann)
        if (length(which(has.pas %in% pas)) < 0.6 * length(pas))
            warnings("Warning: ann: Too few patients has annotation")
        if (length(which(has.pas %in% pas)) < 0.3 * length(pas))
            stop("Error: ann: Too few patients has annotation")
        all.ann = unique(as.vector(as.matrix(ann)))
        all.ann = all.ann[!is.na(all.ann)]
        cl = rainbow(length(all.ann))
        names(cl) <- all.ann
        col.list = lapply(names(ann), function(x) return(cl))
        names(col.list) <- names(ann)
        if (dim(ann)[2] == 1) {
            new.ann = as.data.frame(ann[pas, ])
            row.names(new.ann) <- pas
            names(new.ann) <- names(ann)
        } else {
            new.ann = ann[pas, ]
        }
        ha = HeatmapAnnotation(df = new.ann, annotation_height = 0.2, name = names(ann),
            col = col.list)
    }
    alter_fun = list(background = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h - unit(0.5, "mm"), gp = gpar(fill = "grey",
            col = NA))
    }, Up = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h * 0.33, gp = gpar(fill = up.col, col = NA))
    }, Down = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h * 0.33, gp = gpar(fill = down.col,
            col = NA))
    })
    col = c(Up = up.col, Down = down.col)
    if (!is.null(ha)) {
        if (is.null(col.order)) {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], bottom_annotation = ha,
                alter_fun = alter_fun, col = col, column_title = "", heatmap_legend_param = list(title = "DEG"))
        } else {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], column_order = col.order,
                bottom_annotation = ha, alter_fun = alter_fun, col = col, column_title = "",
                heatmap_legend_param = list(title = "DEG"))
        }
    } else {
        if (is.null(col.order)) {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], alter_fun = alter_fun,
                col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        } else {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], column_order = col.order,
                alter_fun = alter_fun, col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        }
    }
}

#' @rdname Plot.deg
#' @export
Plot <- function(...) {
    UseMethod("Plot")
}

#' Plot the DEGs before or after cross-validation
#'
#' Plot the cross-validated DEGs predicted by \code{\link{deg.specific}}.
#'
#' @import ComplexHeatmap
#' @param input a 'deg.specific' object returned by \code{\link{deg.specific}}
#' @param ann a data.frame for the patient annotation
#' @param col.order the order of column in heatmap
#' @param show.genes the gene ids to plot
#' @param max.n the maximum number of genes to plot
#' @param up.col the color for up-regulated genes
#' @param down.col the color for down-regulated genes
#' @param ... other setting of 'oncoPrint'
#'
#' @author Guofeng Meng
#'
#'
#' @details This function applied the function of oncoPrint from `ComplexHeatmap` to dispaly ownership of the DEGs. The output is a heatmap plots where the genes with maximum observations are showed.
#'
#' @return A heatmap plot
#'
#' @examples
#' Plot(deg,ann.er, max.n=5)
#' Plot(deg.spc, ann.er, max.n=5)
#'
#' @export

Plot.deg.specific <- function(input, ann = NULL, col.order = NULL, show.genes = NULL,
    max.n = 30, up.col = "red", down.col = "blue", ...) {
    if (!is.null(ann) & !is(ann, "data.frame"))
        stop("Error: ann: should be data.frame!")
    ges = input[["decd.input"]][["genes"]]
    pas = input[["decd.input"]][["patients"]]
    dmx = input[["decd.input"]][["deg"]]
    dmx2 = matrix(ncol = length(pas), nrow = length(ges))
    dmx2[, ] = 0
    row.names(dmx2) <- ges
    colnames(dmx2) <- pas
    pa.ids = names(input)
    pa.ids = pa.ids[pa.ids %in% pas]
    for (pa in pa.ids) {
        temp = input[[pa]][["genes"]]
        wh = which(ges %in% temp)
        dmx2[wh, pa] = dmx[wh, pa]
    }

    if (is.null(show.genes)) {
        aa = sort(apply(dmx2, 1, function(x) length(x[x != 0])), decreasing = TRUE)
        show.genes = names(aa[seq_len(min(max.n, dim(dmx2)[1]))])
        if (aa[length(show.genes)] == 0)
            show.genes = names(aa[aa != 0])
    } else {
        show.genes = show.genes[show.genes %in% ges]
        if (length(show.genes) == 0)
            stop("Error: show.genes: cannot recognize the ids")
    }
    mat.deg = t(vapply(show.genes, function(x) {
        y = dmx2[x, ]
        rr = rep("", length(y))
        rr[y == 1] = "Up"
        rr[y == -1] = "Down"
        return(rr)
    }, rep("Up", ncol(dmx2)) ))
    row.names(mat.deg) <- show.genes
    colnames(mat.deg) <- pas
    ha = NULL
    if (!is.null(ann)) {
        has.pas = row.names(ann)
        if (length(which(has.pas %in% pas)) < 0.6 * length(pas))
            warnings("Warning: ann: Too few patients has annotation")
        if (length(which(has.pas %in% pas)) < 0.3 * length(pas))
            stop("Error: ann: Too few patients has annotation")
        all.ann = unique(as.vector(as.matrix(ann)))
        all.ann = all.ann[!is.na(all.ann)]
        cl = rainbow(length(all.ann))
        names(cl) <- all.ann
        col.list = lapply(names(ann), function(x) return(cl))
        names(col.list) <- names(ann)

        if (dim(ann)[2] == 1) {
            new.ann = as.data.frame(ann[pas, ])
            row.names(new.ann) <- pas
            names(new.ann) <- names(ann)
        } else {
            new.ann = ann[pas, ]
        }
        ha = HeatmapAnnotation(df = new.ann, annotation_height = 0.2, name = names(ann),
            col = col.list)
    }
    alter_fun = list(background = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h - unit(0.5, "mm"), gp = gpar(fill = "grey",
            col = NA))
    }, Up = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h * 0.33, gp = gpar(fill = up.col, col = NA))
    }, Down = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h * 0.33, gp = gpar(fill = down.col,
            col = NA))
    })
    col = c(Up = up.col, Down = down.col)
    if (!is.null(ha)) {
        if (is.null(col.order)) {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], bottom_annotation = ha,
                alter_fun = alter_fun, col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        } else {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], column_order = col.order,
                bottom_annotation = ha, alter_fun = alter_fun, col = col, column_title = "",
                heatmap_legend_param = list(title = "DEG"), ...)
        }
    } else {
        if (is.null(col.order)) {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], alter_fun = alter_fun,
                col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        } else {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], column_order = col.order,
                alter_fun = alter_fun, col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        }
    }
}
#' Plot the DEGs before or after cross-validation
#'
#' Plot the cross-validated DEGs predicted by \code{\link{deg.specific}}.
#'
#' @import ComplexHeatmap
#' @import grid
#' @param input a 'deg.specific' object returned by \code{\link{deg.specific}}
#' @param ann a data.frame for the patient annotation
#' @param col.order the order of column in heatmap
#' @param show.genes the gene ids to plot
#' @param max.n the maximum number of genes to plot
#' @param up.col the color for up-regulated genes
#' @param down.col the color for down-regulated genes
#' @param ... other setting of 'oncoPrint'
#'
#' @author Guofeng Meng
#'
#' @references
#'
#' @details This function applied the function of oncoPrint from `ComplexHeatmap` to dispaly ownership of the DEGs. The output is a heatmap plots where the genes with maximum observations are showed.
#'
#' @return A heatmap plot
#'
#' @examples
#' 
#' Plot(deg,ann.er, max.n=5)
#' Plot(deg.spc, ann.er, max.n=5)
#'
#'
#' @export
#'
Plot.deg.specific.test <- function(input, ann = NULL, col.order = NULL, show.genes = NULL,
    max.n = 30, up.col = "red", down.col = "blue", ...) {
    if (!is.null(ann) & !is(ann, "data.frame"))
        stop("Error: ann: should be data.frame!")
    ges = input[["decd.input"]][["genes"]]
    pas = input[["decd.input"]][["patients"]]
    dmx = input[["decd.input"]][["deg"]][ges, pas]
    dmx2 = matrix(ncol = length(pas), nrow = length(ges))
    dmx2[, ] = 0
    row.names(dmx2) <- ges
    colnames(dmx2) <- pas
    pa.ids = names(input)
    pa.ids = pa.ids[pa.ids %in% pas]
    for (pa in pa.ids) {
        temp = input[[pa]]$genes
        wh = which(ges %in% temp)
        dmx2[wh, pa] = dmx[wh, pa]
    }

    if (is.null(show.genes)) {
        aa = sort(apply(dmx2, 1, function(x) length(x[x != 0])), decreasing = TRUE)
        show.genes = names(aa[seq_len(min(max.n, dim(dmx2)[1]))])
        if (aa[length(show.genes)] == 0)
            show.genes = names(aa[aa != 0])
    } else {
        show.genes = show.genes[show.genes %in% ges]
        if (length(show.genes) == 0)
            stop("Error: show.genes: cannot recognize the gene IDs")
    }
    mat.deg = t(vapply(show.genes, function(x) {
        y = dmx2[x, ]
        rr = rep("", length(y))
        rr[y == 1] = "Up"
        rr[y == -1] = "Down"
        return(rr)
    }, rep("Up", ncol(dmx2)) ))
    row.names(mat.deg) <- show.genes
    colnames(mat.deg) <- pas
    ha = NULL
    if (!is.null(ann)) {
        has.pas = row.names(ann)
        if (length(which(has.pas %in% pas)) < 0.6 * length(pas))
            warnings("Warning: ann: Too few patients has annotation")
        if (length(which(has.pas %in% pas)) < 0.3 * length(pas))
            stop("Error: ann: Too few patients has annotation")
        all.ann = unique(as.vector(as.matrix(ann)))
        all.ann = all.ann[!is.na(all.ann)]
        cl = rainbow(length(all.ann))
        names(cl) <- all.ann
        col.list = lapply(names(ann), function(x) {
            return(cl)
        })
        names(col.list) <- names(ann)

        if (dim(ann)[2] == 1) {
            new.ann = as.data.frame(ann[pas, ])
            row.names(new.ann) <- pas
            names(new.ann) <- names(ann)
        } else {
            new.ann = ann[pas, ]
        }
        ha = HeatmapAnnotation(df = new.ann, annotation_height = 0.2, name = names(ann),
            col = col.list)
    }
    alter_fun = list(background = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h - unit(0.5, "mm"), gp = gpar(fill = "grey",
            col = NA))
    }, Up = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h * 0.33, gp = gpar(fill = up.col, col = NA))
    }, Down = function(x, y, w, h) {
        grid.rect(x, y, w - unit(0.5, "mm"), h * 0.33, gp = gpar(fill = down.col,
            col = NA))
    })
    col = c(Up = up.col, Down = down.col)
    if (!is.null(ha)) {
        if (is.null(col.order)) {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], bottom_annotation = ha,
                alter_fun = alter_fun, col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        } else {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], column_order = col.order,
                bottom_annotation = ha, alter_fun = alter_fun, col = col, column_title = "",
                heatmap_legend_param = list(title = "DEG"), ...)
        }
    } else {
        if (is.null(col.order)) {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], alter_fun = alter_fun,
                col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        } else {
            oncoPrint(mat.deg, get_type = function(x) strsplit(x, ";")[[1]], column_order = col.order,
                alter_fun = alter_fun, col = col, column_title = "", heatmap_legend_param = list(title = "DEG"),
                ...)
        }
    }
}