pheatmap有用参数（二）

# Create test matrix（造数据）
set.seed(6)
test = matrix(rnorm(200), 20, 10)
test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3
test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2
test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4
colnames(test) = paste("Test", 1:10, sep = "")
rownames(test) = paste("Gene", 1:20, sep = "")

正文从这儿开端

# Show text within cells
pheatmap(test, display_numbers = TRUE)
pheatmap(test, display_numbers = TRUE, number_format = "\\%.1e")
pheatmap(test, display_numbers = TRUE, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))

• display_numbers = T 即Show text within cells

• number_format 能够格局输出display_number

• 或许爽性自定义一个matrix经过display_numbers参数进行display

# legend（图例）的设置选项
pheatmap(test)  # p1
pheatmap(test, legend_breaks = -1:7)  # p2
pheatmap(test, legend_breaks = 1:6, legend_labels = c("6","6", "6", "6", "6", "6"))  # p3
pheatmap(test, legend_breaks = 9:14, legend_labels = c("6","6", "6", "6", "6", "6"))  # p4

• pheatmap函数会在内部算出legend的数值规模，本例中大概是 -1:7

• 在数值规模内，咱们能够设定legend_breaks，以及对legend_breaks这个label的文本展现

• legend_breaks和legend_labels是有一个对应联系的，不然报错如下

  Error in pheatmap(test, legend_breaks = 1:6, legend_labels =
  c(“6”, “6”, : Lengths of legend_breaks and legend_labels must be
  the same

• 假设咱们的设定规模超出，就如p4所示

# Fix cell sizes and save to file with correct size
pheatmap(test, cellwidth = 15, cellheight = 12, main = "Example heatmap")  # the title of the plot
pheatmap(test, cellwidth = 15, cellheight = 12, fontsize = 8, filename = "test.pdf")  # save to pdf

# Change angle of text in the columns (0, 45, 90, 270 and 315)
pheatmap(test, angle_col = "45")
pheatmap(test, angle_col = "0")

有关annotation

# Generate annotations for rows and columns（先造数据）
annotation_col = data.frame(
                    CellType = factor(rep(c("CT1", "CT2"), 5)), 
                    Time = 1:5
                )
rownames(annotation_col) = paste("Test", 1:10, sep = "")

annotation_row = data.frame(
                    GeneClass = factor(rep(c("Path1", "Path2", "Path3"), c(10, 4, 6)))
                )
rownames(annotation_row) = paste("Gene", 1:20, sep = "")

# Display row and color annotations
pheatmap(test, annotation_col = annotation_col, cluster_cols = F)

pheatmap(test, annotation_col = annotation_col, annotation_legend = FALSE, cluster_cols = F)

pheatmap(test, annotation_row = annotation_row, cluster_rows = F)

• annotation数据首先要组织成dataframe，dataframe中的rownames要和注释项进行对应，
  而column便是要展现的注释条，每个column都会生成一个注释条来显现

• annotation_col/row 默许会有legend合作展现，annotation_legend = FALSE能够去掉legend

# Specify colors （自定义注释条色彩）
ann_colors = list(
    Time = c("white", "firebrick"),
    CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
    GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E")
)

pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors)

pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row, annotation_colors = ann_colors)

• 注释条色彩数据要组织成list（list的灵活性就在此处凸显出来了），
  list中的每个元素名作为对应项（对应前述dataframe中的colnames），
  一起能够进一步为attribute指定色彩，例如
  CT1 = "#1B9E77", CT2 = "#D95F02"

参考资料

pheatmap协助文档