corrected labels

Simulation/causality_figure.R

@@ -16,23 +16,24 @@ for( tag in c("one_causal", "two_causal", "two_opposite"))
   performance = read.csv(paste0("./results/amplitude_effect_", tag, ".csv"), header=TRUE)
   names(performance) = c("id", "amplitude", "correlation", "MAE", "correlation_large", "MAE_large")
   performance = data.table(performance)
+
   head(performance)
   perf = performance[, .(mean(correlation), sd(correlation), mean(MAE), sd(MAE),
   mean(correlation_large), sd(correlation_large), mean(MAE_large), sd(MAE_large), count=.N), by=amplitude]
 
-
   names(perf) = c("amplitude", "correlation", "sd_cor","MAE", "sd_mae", "correlation_large", "sd_correlation_large", "MAE_large", "sd_MAE_large","count")
   names(causal) =c("SNPid", "Beta")
 
   causal["Zscore"] = Zscore[,2]
   c_long = melt(causal, id.var= "SNPid")
 
-  p1 = ggplot(c_long[rev(order(c_long[,2])),], aes(x=SNPid, y=value, color=variable)) + geom_line(size=0.6) +geom_point(size=0.5)
-  p1 = p1 + scale_colour_manual(values=c("orangered", 'royalblue1'))+  theme(legend.position='top',legend.justification="center")
+  p1 = ggplot(c_long[rev(order(c_long[,2])),], aes(x=SNPid, y=value, color=variable)) + geom_line(size=0.6) + geom_point(size=0.5)
+  p1 = p1 + scale_colour_manual(values=c("orangered", 'royalblue1')) + theme(legend.position='top', legend.justification="center")
+
   legend_sig = get_legend(p1)
 
-  pzscore = ggplot(causal, aes(x=SNPid, y=Zscore)) + geom_line(size=0.6, color="royalblue1") +geom_point(size=0.5, color="royalblue1")
-  pcause = ggplot(causal, aes(x=SNPid, y=Beta)) + geom_line(size=0.6, color="orangered") +geom_point(size=0.5, color="orangered")
+  pzscore = ggplot(causal, aes(x=SNPid, y=Zscore)) + geom_line(size=0.6, color="royalblue1") + geom_point(size=0.5, color="royalblue1")
+  pcause = ggplot(causal, aes(x=SNPid, y=Beta)) + geom_line(size=0.6, color="orangered") + geom_point(size=0.5, color="orangered")
 
   legend_sig = get_legend(p1)
 
@@ -53,8 +54,9 @@ for( tag in c("one_causal", "two_causal", "two_opposite"))
 
   p2 =ggplot(perf, aes(x=amplitude, y=correlation)) + geom_point(data=performance, aes(x=amplitude, y=correlation), size=0.1, alpha=0.2) + geom_line(color="royalblue1",size=1) + geom_errorbar(aes(ymin=correlation-sd_cor/(count^0.5), ymax=correlation+sd_cor/(count^0.5)),color="royalblue1", position=position_dodge(0.05))
 
-  p2 = p2 + ylab("")
+  p2 = p2 + ylab("") + xlab("SNP effect size at spike")
   p2
+
   if(tag != "one_causal")
   {
   plot_list[[paste0(tag,"_perf")]] =   p2 + ylim(0,1) + ylab("")
@@ -80,7 +82,7 @@ for( tag in c("one_causal", "two_causal", "two_opposite"))
 }
 
 upper_panel = plot_grid(plot_list[[1]],plot_list[[4]],plot_list[[7]],
-    plot_list[[2]],plot_list[[5]],plot_list[[8]],
+    plot_list[[2]],plot_list[[5]],plot_list[[8]], labels=c("A", "","", "B","",""),label_size=18,
      align="h", nrow=2)
 
 upper_panel_with_leg = plot_grid(legend_sig, upper_panel, rel_heights=c(0.06, 0.94), nrow=2)
@@ -91,14 +93,13 @@ lower_panel = plot_grid(plot_list[[3]],
 
 tiff(filename = "Supp_fig_causal2.tiff",
            width = 900, height = 900, units = "px", pointsize = 12)
-      plot_grid(upper_panel_with_leg, lower_panel, rel_heights=c(0.65,0.35), labels=c("A", "B"), label_size=18, nrow=2)
+      plot_grid(upper_panel_with_leg, lower_panel, rel_heights=c(0.65,0.35), labels=c("", "C"), label_size=18, nrow=2)
 dev.off()
 
 panel_MAE = plot_list_for_reviewer[[tag]]
-
 panel_neuneu = plot_grid(plot_list_for_reviewer[[1]] + ylab("MAE"),plot_list_for_reviewer[[4]],plot_list_for_reviewer[[7]],
                         plot_list_for_reviewer[[2]] + ylab("Correlation_on_large"),plot_list_for_reviewer[[5]],plot_list_for_reviewer[[8]],
-                        plot_list_for_reviewer[[3]]+ ylab("MAE_on_large"),plot_list_for_reviewer[[6]],plot_list_for_reviewer[[9]],
+                        plot_list_for_reviewer[[3]] + ylab("MAE_on_large"),plot_list_for_reviewer[[6]],plot_list_for_reviewer[[9]],
      align="h", nrow=3)
 
 tiff(filename = "for_reviewer_info.tiff",