Principal Component Analysis on gene-expression data

Prions cause neurodegenerative diseases and replicate by the misfolding of the normal benign form of the prion protein. Prion diseases are a public health concern since they lead to very fatal symptoms that are visible after a long incubation time and most cases happen with no recognizable pattern of transmission. Principal component analysis (PCA) was performed on gene expression data in prion-infected mice to analyse gene expression levels in pathways that might play an important role in the pathology of prion diseases. PCA model resulted in an extremely large number of PCs and a lack of clustering according to treatment in PCA plots. Pathway analysis was carried out with GenesetPCA and results suggest that pathways related to vitamin synthesis and glycan degradation are found to be beneficial in decreasing the risk of prion disease. It can be concluded that, PCA might not always be the best way to visualize high-dimensional genomic data. Besides, the limited information on how specific pathways are related to prion disease pathology made it difficult to assess the correctness of the obtained results