Handles unrecorded concentrations using statistical estimates. Options include KNN (K-Nearest Neighbors), median replacement, or half-LOD (Limit of Detection) substitution for low-abundance metabolites.

Applies mathematical functions to stabilize variance and normalize distributions. Log transformation and cube root transformation are commonly used to handle the exponential nature of metabolic concentrations.

Ensures all metabolites are on a comparable scale, preventing high-concentration metabolites from dominating the statistical model. Pareto scaling and Auto-scaling (UV scaling) are standard choices.

Removes unreliable metabolites based on user-defined thresholds. Standard filters include Coefficient of Variation (CV) limits and maximum allowable percentage of missing values.