叠加热图的密度图

Question

我必须绘制一些基因表达值的热图。换句话说，热图的每一行代表 10 个基因的平均值，因此：

• row1 --> mean_genes[1:10],
• row2 --> mean_genes[11:20],
• row3 --> mean_genes[21:30].

到这里，一切正常，因为我知道函数热图。但是，在热图上，我必须一次一行地绘制 1 个基因的表达值的分布（用一条线）：

• row1 --> gene_expression[1],
• row2 --> gene_expression[11],
• row3 --> gene_expression[31].

对所有行以此类推，因为最后我想逐行检查 10 个基因组的表达值以及感兴趣的基因的表达值以进行比较（通过眼睛）。但是我完全不知道如何制作如此复杂的情节。

有什么建议吗？

Answer 1

如果没有示例数据，很难确定你在追求什么，但可能使用 ggplot2 和 geom_tile() 绘图如下（抱歉，它没有修饰，但你可以摆弄它）：

## LIBRARY (must be installed)
require(ggplot2)
require(plyr)

## CREATE THE GENEMAP DATA
geneMap<-data.frame(1:100,expand.grid(1:10,1:10),rnorm(100,6,2))
colnames(geneMap)<-c("ID","X","Y","expr")

## APPEND THE ROWMEANS TO EACH ITEM
rowMean<-ddply(geneMap, "X" ,function(df)mean(df$expr))
geneMap<-merge(geneMap,rowMean,by="X")
colnames(geneMap)<-c("X","ID","Y","expr","rMean")

## CREATE A BASIC TILE WITH FILLED ROWS (FILL BY MEAN, ALPHA BY VALUE)
hmap<-ggplot(data=geneMap, aes(x=X,y=Y)) +        # Basic Plot
      theme_bw() +                                # Basic Theme
      geom_tile(aes(fill=rMean)) +                # Fill the tile by mean
      scale_x_continuous( breaks = 1:10,1) +      # Force ticks 1-10 on x axis
      scale_y_continuous( breaks = 1:10,1) +      # Force ticks 1-10 ony axis
      scale_fill_gradient(low="yellow", high="orange")   # Color the heatmap

hmap <- hmap + annotate("text", x = geneMap$X, y = geneMap$Y, 
                        label = round(geneMap$expr,2))  # Label each point with value

meanSummary<-unique(geneMap[,c("X","rMean")])     # Pull out the means for each row
origSummary<-geneMap[geneMap$Y==1,]               # Pull out the original "seed" vals for each row

hmap<- hmap + annotate("text", x = meanSummary$X, 
                       y = max(geneMap$Y)+1, 
                       label = round(meanSummary$rMean,2)) # Add the mean labels at row end
hmap<- hmap + annotate("text", x = min(geneMap$Y)-1,
                       y = max(geneMap$Y)+1, label = "MEANS") # Label the row

hmap<- hmap + geom_line(aes(x=origSummary$X, 
                            y=origSummary$expr*(max(origSummary$X)/max(origSummary$expr)),
                            size=3, alpha=0.6))   # Add the line plot

# Draw the map & flip is so the rows run horizontally (or not!)
hmap + coord_flip()