Bitte sehen Sie meine Handlung unten:

mein Code:

 > head(data)
              X0      X1      X2       X3       X4       X5       X6        X7        X8        X9
 NM_001001144 6.52334 9.75243 5.62914 6.833650 6.789850 7.421440 8.675330 12.117600 11.551500  7.676900
 NM_001001327 1.89826 3.74708 1.48213 0.590923 2.915120 4.052600 0.758997  3.653680  1.931400  2.487570
 NM_001002267 1.70346 2.72858 2.10879 1.898050 3.063480 4.435810 7.499640  5.038870 11.128700 22.016500
 NM_001003717 6.02279 7.46547 7.39593 7.344080 4.568470 3.347250 2.230450  3.598560  2.470390  4.184450
 NM_001003920 1.06842 1.11961 1.38981 1.054000 0.833823 0.866511 0.795384  0.980946  0.731532  0.949049
 NM_001003953 7.50832 7.13316 4.10741 5.327390 2.311230 1.023050 2.573220  1.883740  3.215150  2.483410

pd <- as.data.frame(scale(t(data)))
pd$Time <- sub("_.*", "", rownames(pd))
pd.m <- melt(pd)
pd.m$variable <- as.numeric(factor(pd.m$variable, levels =     rev(as.character(unique(pd.m$variable))), ordered=F))
p <- ggplot(pd.m, aes(Time, variable))
p  + geom_tile(aes(fill = value)) + scale_fill_gradient2(low=muted("blue"), high=muted("red")) +
  scale_x_discrete(labels=c("0h", "0.25h", "0.5h","1h","2h","3h","6h","12h","24h","48h")) + 
   theme_bw(base_size=20) + theme(axis.text.x=element_text(angle=0, vjust=0.5, hjust=0, size=12),
   axis.text.y=element_text(size=12), strip.text.y=element_text(angle=0, vjust=0.5, hjust=0.5, size=12),
   strip.text.x=element_text(size=12)) + labs(y="Genes", x="Time (h)", fill="")

Gibt es eine Möglichkeit, den Plot zu gruppieren, sodass der Plot die Dynamik im Zeitverlauf anzeigt. Ich möchte das Clustering verwenden, das sich ergibt aus:

 hc.cols <- hclust(dist(t(data)))