Pheatmap annotation colors and border

Question

Pheatmap library(pheatmap) takes annotation_colorsto add the header ID colors on the top of each heatmap column.

I want to add white as column header color with borders. Border can be added by border_color but this function draws borders also to the whole heatmap.

Below is what I have done so far.

library(pheatmap)   
set.seed(123)
df<-data.frame( matrix(sample(30), ncol = 5))
colnames(df)<-LETTERS[1:5]
subj<-c("P1", "P2","P3", "T1", "T2","T3")
rownames(df)<-subj
aka2 = data.frame(ID = factor(rep(c("Pat","Trea"), each=3)))
rownames(aka2)<-subj
aka3 = list(ID = c(Pat = "white", Trea="blue"))
pheatmap(t(scale(df)),
         annotation_col = aka2, 
         annotation_colors = aka3[1],
         annotation_legend = FALSE,
         gaps_col =  3,
         show_colnames = T, show_rownames = T, cluster_rows = F, 
         cluster_cols = F, legend = TRUE, 
         clustering_distance_rows = "euclidean", border_color = FALSE)

Patriarchate

Please provide a reproducible example showing how far you got. – Errand

Your code is showing that you are trying to display ID as black or blue not white. The ID annotation row is white because the rownames of aka2 do not match the rownames of df. Also, if I remove border_color option from your example, the ID annotation row has a grey border surrounding white. So, on multiple levels, your question does not make sense. Please clarify your question/problem. – Lactary

I have rephrased and clarified better the question – Patriarchate

You say "but the color space remain empty." What do you expect to happen? Do you want Pat IDs to be white and Trea IDs to be blue? If so, reread my comment above; you need to set the rownames of aka2 to that of df. – Lactary

Yes, you are right, I missed that part in this version. Now you can see 3 heatmap columns are blue and 3 are white; borders are needed to distinguish white labels. – Patriarchate

Answer 1

I use grid functions to edit the relevant grob:

library(pheatmap)   
set.seed(123)
df<-data.frame( matrix(sample(30), ncol = 5))
colnames(df)<-LETTERS[1:5]
subj<-c("P1", "P2","P3", "T1", "T2","T3")
rownames(df)<-subj
aka2 = data.frame(ID = factor(rep(c("Pat","Trea"), each=3)))
rownames(aka2)<-subj
aka3 = list(ID = c(Pat = "white", Trea="blue"))

pheatmap(t(scale(df)),
         annotation_col = aka2, 
         annotation_colors = aka3[1],
         annotation_legend = FALSE,
         gaps_col =  3,
         show_colnames = T, show_rownames = T, cluster_rows = F, 
         cluster_cols = F, legend = TRUE, 
         clustering_distance_rows = "euclidean", border_color = FALSE)

# Edit the relevant grob
library(grid)
grid.ls(grid.force()) # "col_annotation" looks like it's the one to edit
grid.gedit("col_annotation", gp = gpar(col="grey70"))

Applying grid.gget("col_annotation")$gp to the original heatmap shows that col_annotation does have a gp slot with fill set but no col. After the edit, both fill and col are set.

Mi

Answer 2

I tried very hard to edit the grobs to add border color only on the annotations, but I think the only way is to modify the pheatmap function as well as the underlying heatmap_motor. Here is the pheatmap2 and heatmap_motor2 functions. The only changes is that pheatmap2 calls heatmap_motor2 and this line border_color="gray" in heatmap_motor2. You can find it about 2/3 of the way in heatmap_motor2.

pheatmap2

pheatmap2 <-function (mat, color = colorRampPalette(rev(brewer.pal(n = 7,
    name = "RdYlBu")))(100), kmeans_k = NA, breaks = NA, border_color = "grey60",
    cellwidth = NA, cellheight = NA, scale = "none", cluster_rows = TRUE,
    cluster_cols = TRUE, clustering_distance_rows = "euclidean",
    clustering_distance_cols = "euclidean", clustering_method = "complete",
    clustering_callback = identity2, cutree_rows = NA, cutree_cols = NA,
    treeheight_row = ifelse(cluster_rows, 50, 0), treeheight_col = ifelse(cluster_cols,
        50, 0), legend = TRUE, legend_breaks = NA, legend_labels = NA,
    annotation_row = NA, annotation_col = NA, annotation = NA,
    annotation_colors = NA, annotation_legend = TRUE, drop_levels = TRUE,
    show_rownames = T, show_colnames = T, main = NA, fontsize = 10,
    fontsize_row = fontsize, fontsize_col = fontsize, display_numbers = F,
    number_format = "%.2f", number_color = "grey30", fontsize_number = 0.8 *
        fontsize, gaps_row = NULL, gaps_col = NULL, labels_row = NULL,
    labels_col = NULL, filename = NA, width = NA, height = NA,
    silent = FALSE, ...)
{
    if (is.null(labels_row)) {
        labels_row = rownames(mat)
    }
    if (is.null(labels_col)) {
        labels_col = colnames(mat)
    }
    mat = as.matrix(mat)
    if (scale != "none") {
        mat = scale_mat(mat, scale)
        if (is.na2(breaks)) {
            breaks = generate_breaks(mat, length(color), center = T)
        }
    }
    if (!is.na(kmeans_k)) {
        km = kmeans(mat, kmeans_k, iter.max = 100)
        mat = km$centers
        t = table(km$cluster)
        labels_row = sprintf("Cluster: %s Size: %d", names(t),
            t)
    }
    else {
        km = NA
    }
    if (is.matrix(display_numbers) | is.data.frame(display_numbers)) {
        if (nrow(display_numbers) != nrow(mat) | ncol(display_numbers) !=
            ncol(mat)) {
            stop("If display_numbers provided as matrix, its dimensions have to match with mat")
        }
        display_numbers = as.matrix(display_numbers)
        fmat = matrix(as.character(display_numbers), nrow = nrow(display_numbers),
            ncol = ncol(display_numbers))
        fmat_draw = TRUE
    }
    else {
        if (display_numbers) {
            fmat = matrix(sprintf(number_format, mat), nrow = nrow(mat),
                ncol = ncol(mat))
            fmat_draw = TRUE
        }
        else {
            fmat = matrix(NA, nrow = nrow(mat), ncol = ncol(mat))
            fmat_draw = FALSE
        }
    }
    if (cluster_rows) {
        tree_row = cluster_mat(mat, distance = clustering_distance_rows,
            method = clustering_method)
        tree_row = clustering_callback(tree_row, mat)
        mat = mat[tree_row$order, , drop = FALSE]
        fmat = fmat[tree_row$order, , drop = FALSE]
        labels_row = labels_row[tree_row$order]
        if (!is.na(cutree_rows)) {
            gaps_row = find_gaps(tree_row, cutree_rows)
        }
        else {
            gaps_row = NULL
        }
    }
    else {
        tree_row = NA
        treeheight_row = 0
    }
    if (cluster_cols) {
        tree_col = cluster_mat(t(mat), distance = clustering_distance_cols,
            method = clustering_method)
        tree_col = clustering_callback(tree_col, t(mat))
        mat = mat[, tree_col$order, drop = FALSE]
        fmat = fmat[, tree_col$order, drop = FALSE]
        labels_col = labels_col[tree_col$order]
        if (!is.na(cutree_cols)) {
            gaps_col = find_gaps(tree_col, cutree_cols)
        }
        else {
            gaps_col = NULL
        }
    }
    else {
        tree_col = NA
        treeheight_col = 0
    }
    attr(fmat, "draw") = fmat_draw
    if (!is.na2(legend_breaks) & !is.na2(legend_labels)) {
        if (length(legend_breaks) != length(legend_labels)) {
            stop("Lengths of legend_breaks and legend_labels must be the same")
        }
    }
    if (is.na2(breaks)) {
        breaks = generate_breaks(as.vector(mat), length(color))
    }
    if (legend & is.na2(legend_breaks)) {
        legend = grid.pretty(range(as.vector(breaks)))
        names(legend) = legend
    }
    else if (legend & !is.na2(legend_breaks)) {
        legend = legend_breaks[legend_breaks >= min(breaks) &
            legend_breaks <= max(breaks)]
        if (!is.na2(legend_labels)) {
            legend_labels = legend_labels[legend_breaks >= min(breaks) &
                legend_breaks <= max(breaks)]
            names(legend) = legend_labels
        }
        else {
            names(legend) = legend
        }
    }
    else {
        legend = NA
    }
    mat = scale_colours(mat, col = color, breaks = breaks)
    if (is.na2(annotation_col) & !is.na2(annotation)) {
        annotation_col = annotation
    }
    if (!is.na2(annotation_col)) {
        annotation_col = annotation_col[colnames(mat), , drop = F]
    }
    if (!is.na2(annotation_row)) {
        annotation_row = annotation_row[rownames(mat), , drop = F]
    }
    annotation = c(annotation_row, annotation_col)
    annotation = annotation[unlist(lapply(annotation, function(x) !is.na2(x)))]
    if (length(annotation) != 0) {
        annotation_colors = generate_annotation_colours(annotation,
            annotation_colors, drop = drop_levels)
    }
    else {
        annotation_colors = NA
    }
    if (!show_rownames) {
        labels_row = NULL
    }
    if (!show_colnames) {
        labels_col = NULL
    }
    gt = heatmap_motor2(mat, border_color = border_color, cellwidth = cellwidth,
        cellheight = cellheight, treeheight_col = treeheight_col,
        treeheight_row = treeheight_row, tree_col = tree_col,
        tree_row = tree_row, filename = filename, width = width,
        height = height, breaks = breaks, color = color, legend = legend,
        annotation_row = annotation_row, annotation_col = annotation_col,
        annotation_colors = annotation_colors, annotation_legend = annotation_legend,
        main = main, fontsize = fontsize, fontsize_row = fontsize_row,
        fontsize_col = fontsize_col, fmat = fmat, fontsize_number = fontsize_number,
        number_color = number_color, gaps_row = gaps_row, gaps_col = gaps_col,
        labels_row = labels_row, labels_col = labels_col, ...)
    if (is.na(filename) & !silent) {
        grid.newpage()
        grid.draw(gt)
    }
    invisible(list(tree_row = tree_row, tree_col = tree_col,
        kmeans = km, gtable = gt))
}

heatmap_motor2

heatmap_motor2 <-function (matrix, border_color, cellwidth, cellheight, tree_col,
    tree_row, treeheight_col, treeheight_row, filename, width,
    height, breaks, color, legend, annotation_row, annotation_col,
    annotation_colors, annotation_legend, main, fontsize, fontsize_row,
    fontsize_col, fmat, fontsize_number, number_color, gaps_col,
    gaps_row, labels_row, labels_col, ...)
{
    lo = lo(coln = labels_col, rown = labels_row, nrow = nrow(matrix),
        ncol = ncol(matrix), cellwidth = cellwidth, cellheight = cellheight,
        treeheight_col = treeheight_col, treeheight_row = treeheight_row,
        legend = legend, annotation_col = annotation_col, annotation_row = annotation_row,
        annotation_colors = annotation_colors, annotation_legend = annotation_legend,
        main = main, fontsize = fontsize, fontsize_row = fontsize_row,
        fontsize_col = fontsize_col, gaps_row = gaps_row, gaps_col = gaps_col,
        ...)
    res = lo$gt
    mindim = lo$mindim
    if (!is.na(filename)) {
        if (is.na(height)) {
            height = convertHeight(gtable_height(res), "inches",
                valueOnly = T)
        }
        if (is.na(width)) {
            width = convertWidth(gtable_width(res), "inches",
                valueOnly = T)
        }
        r = regexpr("\\.[a-zA-Z]*$", filename)
        if (r == -1)
            stop("Improper filename")
        ending = substr(filename, r + 1, r + attr(r, "match.length"))
        f = switch(ending, pdf = function(x, ...) pdf(x, ...),
            png = function(x, ...) png(x, units = "in", res = 300,
                ...), jpeg = function(x, ...) jpeg(x, units = "in",
                res = 300, ...), jpg = function(x, ...) jpeg(x,
                units = "in", res = 300, ...), tiff = function(x,
                ...) tiff(x, units = "in", res = 300, compression = "lzw",
                ...), bmp = function(x, ...) bmp(x, units = "in",
                res = 300, ...), stop("File type should be: pdf, png, bmp, jpg, tiff"))
        f(filename, height = height, width = width)
        gt = heatmap_motor(matrix, cellwidth = cellwidth, cellheight = cellheight,
            border_color = border_color, tree_col = tree_col,
            tree_row = tree_row, treeheight_col = treeheight_col,
            treeheight_row = treeheight_row, breaks = breaks,
            color = color, legend = legend, annotation_col = annotation_col,
            annotation_row = annotation_row, annotation_colors = annotation_colors,
            annotation_legend = annotation_legend, filename = NA,
            main = main, fontsize = fontsize, fontsize_row = fontsize_row,
            fontsize_col = fontsize_col, fmat = fmat, fontsize_number = fontsize_number,
            number_color = number_color, labels_row = labels_row,
            labels_col = labels_col, gaps_col = gaps_col, gaps_row = gaps_row,
            ...)
        grid.draw(gt)
        dev.off()
        return(gt)
    }
    if (mindim < 3)
        border_color = NA
    if (!is.na(main)) {
        elem = draw_main(main, fontsize = 1.3 * fontsize, ...)
        res = gtable_add_grob(res, elem, t = 1, l = 3, name = "main")
    }
    if (!is.na2(tree_col) & treeheight_col != 0) {
        elem = draw_dendrogram(tree_col, gaps_col, horizontal = T)
        res = gtable_add_grob(res, elem, t = 2, l = 3, name = "col_tree")
    }
    if (!is.na2(tree_row) & treeheight_row != 0) {
        elem = draw_dendrogram(tree_row, gaps_row, horizontal = F)
        res = gtable_add_grob(res, elem, t = 4, l = 1, name = "row_tree")
    }
    elem = draw_matrix(matrix, border_color, gaps_row, gaps_col,
        fmat, fontsize_number, number_color)
    res = gtable_add_grob(res, elem, t = 4, l = 3, clip = "off",
        name = "matrix")
    if (length(labels_col) != 0) {
        pars = list(labels_col, gaps = gaps_col, fontsize = fontsize_col,
            ...)
        elem = do.call(draw_colnames, pars)
        res = gtable_add_grob(res, elem, t = 5, l = 3, clip = "off",
            name = "col_names")
    }
    if (length(labels_row) != 0) {
        pars = list(labels_row, gaps = gaps_row, fontsize = fontsize_row,
            ...)
        elem = do.call(draw_rownames, pars)
        res = gtable_add_grob(res, elem, t = 4, l = 4, clip = "off",
            name = "row_names")
    }
    if (!is.na2(annotation_col)) {
        converted_annotation = convert_annotations(annotation_col,
            annotation_colors)
        elem = draw_annotations(converted_annotation, border_color="gray", #Modified here
            gaps_col, fontsize, horizontal = T)
        res = gtable_add_grob(res, elem, t = 3, l = 3, clip = "off",
            name = "col_annotation")
        elem = draw_annotation_names(annotation_col, fontsize,
            horizontal = T)
        res = gtable_add_grob(res, elem, t = 3, l = 4, clip = "off",
            name = "row_annotation_names")
    }
    if (!is.na2(annotation_row)) {
        converted_annotation = convert_annotations(annotation_row,
            annotation_colors)
        elem = draw_annotations(converted_annotation, border_color,
            gaps_row, fontsize, horizontal = F)
        res = gtable_add_grob(res, elem, t = 4, l = 2, clip = "off",
            name = "row_annotation")
        if (length(labels_col) != 0) {
            elem = draw_annotation_names(annotation_row, fontsize,
                horizontal = F)
            res = gtable_add_grob(res, elem, t = 5, l = 2, clip = "off",
                name = "row_annotation_names")
        }
    }
    annotation = c(annotation_col[length(annotation_col):1],
        annotation_row[length(annotation_row):1])
    annotation = annotation[unlist(lapply(annotation, function(x) !is.na2(x)))]
    if (length(annotation) > 0 & annotation_legend) {
        elem = draw_annotation_legend(annotation, annotation_colors,
            border_color, fontsize = fontsize, ...)
        t = ifelse(is.null(labels_row), 4, 3)
        res = gtable_add_grob(res, elem, t = t, l = 6, b = 5,
            clip = "off", name = "annotation_legend")
    }
    if (!is.na2(legend)) {
        elem = draw_legend(color, breaks, legend, fontsize = fontsize,
            ...)
        t = ifelse(is.null(labels_row), 4, 3)
        res = gtable_add_grob(res, elem, t = t, l = 5, b = 5,
            clip = "off", name = "legend")
    }
    return(res)
}

It is then important to add these two new functions to the pheatmap environment. pheatmap uses functions that can only be found in it's own environment.

environment(pheatmap2) <- asNamespace('pheatmap')
environment(heatmap_motor2) <- asNamespace('pheatmap')

With the gray borders to the annotations using pheatmap2:

library(pheatmap)
set.seed(123)
df<-data.frame( matrix(sample(30), ncol = 5))
colnames(df)<-LETTERS[1:5]
subj<-c("P1", "P2","P3", "T1", "T2","T3")
rownames(df)<-subj
aka2 = data.frame(ID = factor(rep(c("Pat","Trea"), each=3)))
rownames(aka2)<-subj
aka3 = list(ID = c(Pat = "white", Trea="blue"))
pheatmap2(t(scale(df)),
         annotation_col = aka2,
         annotation_colors = aka3[1], #aka3[1]
         annotation_legend = FALSE,
         gaps_col =  3,
         show_colnames = T, show_rownames = T, cluster_rows = F,
         cluster_cols = F, legend = TRUE,
         clustering_distance_rows = "euclidean", border_color = FALSE)

Laughton

i have similar question #73007645 which is what you have done here modifying the function – Deposal

Answer 3

Pheatmap annotation_col/annotation_row and borders and annotation_colors

Just to make a few comments that may be a bit off the topic here, but relevant in the context of this question and might save someone some trouble.

1. If you are interested in having borders for all cells in the heatmap after setting annotation_col or annotation_row you must specify explicitly cellheight and cellwidth above certain levels (I used cellwidth = 3, cellheight=12).

2. The syntax for annotation_color is somewhat complex and requires a list of named vectors with named components. For example:

   annotation_col = data.frame("Cell_of_Origin"=factor(dta.disc$cell.origin,exclude=NULL,labels=c("GCB","non_GCB","Unclassifiable")))
   rownames(annotation_col)=dta.disc$id
   annotation_colors = list(Cell_of_Origin=c(GCB="red",non_GCB="green",Unclassifiable="yellow"))[1]
   

Where Cell_of_Origin is my annotation_col variable and GCB,non_GCB, Unclassifiable are the levels of the factor.

3. It seems strange to me to add a grid for annotated classes and not grid for the clusters (i.e. the subclasses may be distributed 'weirdly' within the clusters). One option I played with was to generate a dendrogram for each subclass separately and then merge the dendrograms together. In such a case you could add gaps between clusters using the cutree_cols / cutree_row options.The results weren't great but this might be a direction to explore.

   dend_gcb = reorder(as.dendrogram(hclust(dist(as.matrix(t(dta.disc[dta.disc$cell.origin=="gcb",vars_reduced]))))),agglo.FUN=mean)
   dend_ngcb = reorder(as.dendrogram(hclust(dist(as.matrix(t(dta.disc[dta.disc$cell.origin=="non-gcb",vars_reduced]))))),agglo.FUN=mean)
   dend_uncls =reorder(as.dendrogram(hclust(dist(as.matrix(t(dta.disc[is.na(dta.disc$cell.origin),vars_reduced]))))),agglo.FUN=mean)
   dend=merge(merge(dend_gcb,dend_ngcb),dend_uncls)
   

Hypercriticism