Uses Z-score based calculations to identify metabolites that deviate significantly from the mean. This method is crucial for detecting sample preparation errors or biological anomalies.

Flags metabolites that show identical concentration values across multiple samples. While rare in biology, this often indicates technical replicas, data entry errors, or sensor saturation issues.

Evaluates data against the Limit of Detection (LOD). High percentages of values below LOD can skew statistical results and may require imputation or exclusion from certain downstream analyses.

Compares observed concentrations against physiologically expected ranges documented in the Human Metabolome Database (HMDB). Values outside these ranges are flagged for review.

Adjusts metabolite concentrations based on Creatinine levels or other normalization factors. This accounting for hydration levels is essential for accurate comparative analysis of urine samples.