Hello everyone!

I'm doing PCA (principal Component Analysis) on a set of 1000 genes in 4 different samples to see if there's any split in the data. My data looks like this:

id       sample1     sample2     sample3     sample4
gene1    2           0           1           1
gene2    1           2           0           3 
gene3    2           2           4           2
gene4    3           1           7           0

My code is very simple:

data<-read.csv("exp.csv")

matrix<-data.matrix(data)

pca<- prcomp(matrix[,2:4], scale.=T)

library(ggplot2)

# create data frame with scores
scores = as.data.frame(pca$x)

# plot of observations
ggplot(data = scores, aes(x = PC1, y = PC2, label = rownames(exp))) +
  geom_hline(yintercept = 0, colour = "gray65") +
  geom_vline(xintercept = 0, colour = "gray65") +
  geom_text(colour = "tomato", alpha = 0.8, size = 4) +
  ggtitle("PCA plot")

When I plot PC1 and PC2 I clearly see a separation so the genes are divided into 2 big groups but how can I see what the constituent genes of these 2 clusters are? because in the plot lots of genes overlap with each other and therefore its difficult to make out the gene names just from the plot. How can I extract these from PCA results and save it as a text file?

EDIT: For the above code, can someone tell me as to how I can colour the dots in the plot according to the sample? I tried changing colour parameter in ggplot but its not working.

Thanks!!