Metabolomics#
Tutorials for the omicverse.metabol module — downstream analysis of peak-intensity tables
produced by XCMS / MZmine / MS-DIAL / MetaboAnalyst. Covers QC, batch correction, imputation,
normalization, two-group and multi-factor (time-series, mixed-effects) statistics, biomarker
discovery, correlation analysis, pathway enrichment (ORA + GSEA + mummichog), lipidomics
(LIPID MAPS + LION), and multi-omics integration with RNA-seq via MOFA+.
- Metabolomics preprocessing and univariate statistics
- Multivariate discrimination with PLS-DA and OPLS-DA
- Metabolite-set enrichment analysis (MSEA)
- Untargeted LC-MS and mummichog pathway inference
- Lipidomics with LIPID MAPS and LION
- Batch effect and drift correction for LC-MS
- Multi-factor designs — ASCA and linear mixed models
- Biomarker discovery — univariate AUC + multivariate panel
- Differential correlation — DGCA
- Multi-omics integration — metabolomics + RNA-seq with MOFA
- Real-data case study — MTBLS1 (urine NMR, Type 2 Diabetes)