basic principal components analysis and visualization in R

pca.R

# Basic PCA example
# use www.createdatasol.com for 
# an advanced user interface 

#required packages for plotting
library(ggplot2)
library(ggrepel)

#load data
data<-read.csv('~/Sampledata.csv', 
               header = TRUE,stringsAsFactors = FALSE)

#split numeric and text
is_num<-!sapply(data,class) %in% c('character','factor')

#calculate principal components
pca<-prcomp(data[,is_num]) 

# get sample scores and
# add meta data for visualization
plot_data<-cbind(data[,!is_num],pca$x)

#plot scores
ggplot(plot_data, aes(x=PC1,y=PC2)) +
  geom_point(aes(color=Label,size=Age),alpha=.75) +
  geom_text_repel(aes(label=ID),size=1.5) +
  theme_classic()