I would be careful as to what type of data to be used in PCA, as this algorithm is sensitive to types of data (nominal, ordinal, categorical, interval). Especially in this part, because it is a distance based algorithm.
distance_matrix <- as.matrix(dist(scale(mtcars)))
pca <- prcomp(distance_matrix)
What was puzzling me, is a simple content question: What is the outlier in your case? When looking for outliers, one should have a clear goal as to how to define an outlier (in content sense), so that the part of, "what one would be looking for" is made simpler and what are the thresholds values for such outliers.
Tomaž Kaštrun | twitter: @tomaz_tsql | Github: https://github.com/tomaztk | blog: https://tomaztsql.wordpress.com/