用ggplot2画heatmap
> library(ggplot2)
Loading required package: proto
Loading required package: grid
Loading required package: reshape
Loading required package: plyr
Loading required package: digest
> sample.data <- matrix(rnorm(500), 50, 10)
> sample.data <- as.data.frame(sample.data)
> sample.data <- cbind(paste("g", 1:50, sep=""), sample.data)
> colnames(sample.data) <- c("GeneName", paste("t", 1:10, sep=""))
> head(sample.data)
GeneName t1 t2 t3 t4 t5 t6
1 g1 0.6506507 2.2511342 -0.3816986 0.3280272 0.4610605 1.5809543
2 g2 -0.6905213 0.3381060 -0.7077111 1.4078910 0.2933683 -0.1066459
3 g3 0.3541356 0.4541696 -1.6335950 0.4263433 -0.5189055 0.5252583
4 g4 -0.7536498 -0.6576679 -1.2011061 0.2127903 -0.2037233 -0.6236748
5 g5 0.1589113 0.4053087 -1.1849440 -0.2635171 2.0520325 -0.2831023
6 g6 0.4785667 0.2277287 -0.5114406 0.3719895 0.7284306 0.1884368
t7 t8 t9 t10
1 -1.3000891 0.5892476 1.590302760 -0.3231108
2 2.0824780 0.9929615 -0.133183908 0.8461574
3 0.5556600 -1.2984789 0.000519446 0.3543165
4 1.5932854 0.3699189 0.972156471 -0.5041644
5 0.7586054 1.3547863 1.778556359 1.3227048
6 -0.1165529 1.2721110 1.082750129 -0.9139294
> sample.data <- melt(sample.data)
Using GeneName as id variables
> head(sample.data)
GeneName variable value
1 g1 t1 0.6506507
2 g2 t1 -0.6905213
3 g3 t1 0.3541356
4 g4 t1 -0.7536498
5 g5 t1 0.1589113
6 g6 t1 0.4785667
> p <- ggplot(sample.data, aes(variable, GeneName))
> p <- p + geom_tile(aes(fill = value),
+ colour = "white") + scale_fill_gradient(low="white", high="steelblue")
> p
> library(Cairo)
> CairoPNG("d:/heatmap0206.png", 800,800)
> p
> dev.off()
windows
2
把variable和GeneName分别作为x轴和y轴，然后按着value的值去填充颜色。
