2.6 Data Processing
Waters raw data files generated from the metabolomics analysis were converted to mzData files using the convert.waters.raw R package. Using the isotopologue parameter optimization (IPO) R package, the quality control pooled sample injections were used to find the optimal peak processing parameters, retention time corrections and grouping parameters. Parameters generated from IPO were used for XCMS processing of metabolomics data. The CAMERA package was applied to XCMS processed features to annotate possible isotopes and adducts. The resulting data was subsequently normalized to internal standards, and features with >30% relative standard deviation (rsd) within quality control injections were excluded from analysis. Urine features were normalized to their corresponding urinary creatinine and internal standard signals, to account for differences in urine concentration. Using the CAMERA package, features were grouped based on Pearson correlation coefficients and retention time into “pcgroups”. Within each pcgroup, only the feature with the highest mean raw intensity was kept for further data analysis. Duplicate features found in both the untargeted and derivatized experiments were removed from the derivatized dataset before analysis. The raw intensity values of all features were log transformed using MetaboAnalyst 5.0, to remove heteroscedasticity and correct for skewed data distribution. Any 0 values during log transformation were treated as 1/5 of the minimum intensity values of each feature. Log transformed feature intensity values were used for all analyses unless stated otherwise.