*4.6. Data Processing*

The generated metabolomics profiling data sets were processed by the control software of the Xcalibur® mass spectrometer and saved in a specific data format (\*.raw). The first step was to convert data from Excalibur-specific raw files to open format files (\*.mzXML) using MS Convertor software (ProteoWizard) [48]. Subsequently, metabolomics data were processed using the XCMS Online web version platform [49]. All results and images for processing were downloaded as zip files for offline analysis, including putative METLIN identities for each metabolite.

#### *4.7. Statistical Data Analysis*

Univariate and multivariate statistical analysis was performed in an interactive manner using statistical software Statistica (Version 13.3, TIBCO Software, Palo Alto, CA, USA) and R-statistic software in the Metabol package [50]. The data for processing was exported in the form of data matrix X (n × m) from an Excel file (output from data processing) to individual statistical programs. Before the application of multivariate statistical analysis, exploratory data analysis was conducted [51]. This included the assessment of primarily found outlier objects (or features thereof), assuming linear relationship and verifying the data provided (normality, non-correlation, homogeneity). Subsequently, the data matrices were standardized by two different methods. In the first case, the data were transformed by mean centering [37], and in the second case, they were transformed by probabilistic quotient normalization PQN [38,52] and a natural logarithm was applied for their scaling before

subsequent statistical analysis. Multidimensional statistical methods, such as principal component analysis (PCA), cluster analysis (CA), and orthogonal partial least squares discriminant analysis (OPLS-DA), were used to statistically evaluate data obtained from non-targeted metabolomics analyses.
