Añadida función ggcorrplot.

R/ggcorrplot.R

@@ -0,0 +1,18 @@
+ggcorrplot<-function(df, var){
+  m.df<-df %>% spread(Cyt, Value) %>% select(-pats)
+  mcor<-cor(m.df, m.df, use="pairwise.complete.obs") # Por defecto usa el método de Pearson.
+  mpval<-Hmisc::rcorr(as.matrix(m.df))$P
+
+  df<-mcor %>% as.data.frame() %>% add_column(Var1=rownames(mcor),.before=1) %>%
+    gather(Var2, Value, -Var1)
+  df.pval<-mpval %>% as.data.frame() %>% add_column(Var1=rownames(mpval),.before=1) %>%
+    gather(Var2, Value, -Var1)
+
+  order<- mcor %>% as.data.frame() %>% add_column(Var1=rownames(mcor),.before=1) %>% clustsort
+
+  ggplot(df, aes(Var1, Var2, fill=Value))+
+    scale_x_discrete(limits=order$x)+
+    scale_y_discrete(limits=order$y)+
+    theme_heatmap(line.color="black")+
+    geom_text(data=df.pval, aes(label=round(Value, 2)))
+}

R/theme_heatmap.R

@@ -1,5 +1,5 @@
-theme_heatmap<-function(x){
-  list(geom_tile(),
+theme_heatmap<-function(x,line.color="#FFFFFF00"){
+  list(geom_tile(color=line.color),
        scale_fill_gradientn(colors=col2(200)),
        theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5),
              panel.background = element_blank(),