Version Compatibility

Reference examples tested with: limma 3.58+, ashr 2.2+, scipy 1.12+, statsmodels 0.14+, numpy 1.26+, pandas 2.1+, mixOmics 6.28+, ggplot2 3.5+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name to verify parameters

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Metabolomics Statistical Analysis

Processing Pipeline

Standard pipeline: zero/missing handling -> log2 transformation -> normalization -> statistical testing. Fold change and statistical tests operate on log2-transformed, normalized but unscaled data. Pareto or auto-scaling distorts fold change magnitudes -- apply only for multivariate methods (PCA, PLS-DA).

Zero and Missing Value Handling