4.3.2. Multivariate Methods
All multivariate analyses were done in SIMCA software v.17.0 (Sartorius Stedim Data Analytics AB, Umeå, Sweden) and no samples were excluded from any of the analyses. Principal component analysis (PCA) models and orthogonal projections to latent structures (OPLS) were used to explore clustering patterns of observations and trends in the data in relation to known factors and outliers (Class discriminating oxylipins of interest from the OPLS-EP and OPLS-DA models were selected if loadings w ≥ ±0.1 and if they were among the twenty highest variable importance (VIP) scores.