transfer from old repo

1 PA Decline/archive/generation_1/PCA.R

@@ -0,0 +1,74 @@
+## ItMLiHSmar2022
+## PCA.R, child script
+## Principal components analysis for data visualisation
+## Andreas Gammelgaard Damsbo, agdamsbo@clin.au.dk
+
+
+## ====================================================================
+## Step 0: data wrangling
+## ====================================================================
+# source("data_format.R")
+
+X1<-X %>% dplyr::mutate(across(where(is.factor), as.numeric))
+
+pc.out<-prcomp(X1, center=TRUE, scale = TRUE)
+
+pc.sum<-summary(pc.out)
+
+## ====================================================================
+## Step 1: plotting
+## ====================================================================
+Xy$group<-factor(Xy$group,labels = c("No decline", "Decline"))
+
+library(ggfortify)
+ppc12 <- autoplot(pc.out,
+                  data = Xy,
+                  x=1,
+                  y=2,
+                  colour = 'group')+
+  labs(title = "PC1 and PC2",
+       colour = "Outcome")
+ppc13 <- autoplot(pc.out,
+                  data = Xy,
+                  x=1,
+                  y=3,
+                  colour = 'group')+
+  labs(title = "PC1 and PC3",
+       colour = "Outcome")
+ppc23 <- autoplot(pc.out,
+                  data = Xy,
+                  x=2,
+                  y=3,
+                  colour = 'group')+
+  labs(title = "PC2 and PC3",
+       colour = "Outcome")
+
+# Scree plot
+pscr<-tibble(x=1:dim(pc.sum$importance)[2],
+             Proportion=pc.sum$importance[2,],
+             Cumulative=pc.sum$importance[3,])%>%
+  pivot_longer(cols=-x)%>%
+  ggplot(aes(x=x,y=value,color=name))+
+  geom_line()+
+  geom_point()+
+  ylim(0,1)+
+  labs(title = "Scree plot",
+       color= "Variance")+
+  ylab("Variance")+
+  xlab("Principal components")
+
+## ====================================================================
+## Step 2: merge plots
+## ====================================================================
+library(patchwork)
+pca22<-ppc12+
+  theme(legend.position="none")+
+  ppc13+
+  ppc23+theme(legend.position="none")+
+  pscr+ 
+  plot_layout(ncol=2)+
+  plot_annotation(title = 'Principal component visualisation',
+                  tag_levels = "A")
+
+# pca22
+