Experimental design
Study structure, biological replication, batch design, randomization, controls, sample storage requirements, and planning for downstream statistical analysis.
Metabolomics Training Program
Practical training across the complete metabolomics workflow
The Mass Spectrometry Core offers metabolomics training for scientists at all career levels, from investigators who are new to mass spectrometry to researchers seeking more advanced experience with targeted and untargeted small-molecule workflows.
Program overview
Training built around real metabolomics workflows
Courses are designed to connect experimental design, analytical measurement, data processing, and interpretation rather than treating each step as an isolated technique. Training covers both targeted quantitative analysis and untargeted discovery workflows, with emphasis on the decisions that affect data quality, reproducibility, and biological interpretation.
For scientists at different levels of experience
The curriculum covers the complete metabolomics workflow, with instruction presented to support participants with different levels of experience and research backgrounds.
Introductory and advanced concepts
Hands-on training in sample preparation, LCMS data acquisition, and data analysis
Advanced instruction in quantitative and untargeted analysis
Study-specific training tailored to research questions
Training topics
From study design to biological interpretation
The curriculum covers the complete metabolomics workflow, with instruction tailored to the needs and research goals of the trainee.
Sample preparation
Preparation strategies for small-molecule analysis, extraction considerations, sample handling, internal standards, and approaches that support reproducible LC-MS data.
Quality control
Pooled QC samples, blanks, internal standards, reproducibility assessment, analytical drift, coefficient of variation, and identification of data-quality problems.
Absolute & relative quantitation
Calibration- and internal standard-based absolute quantitation, relative abundance quantitation, quantitative method performance, and interpretation of results.
Data filtering
Feature quality assessment, missing-value and imputation considerations, reproducibility filters, blank filtering, normalization concepts, batch correction and preparation of data for statistical analysis.
Statistical analysis
Univariate and multivariate analysis, multiple-testing correction, effect size, clustering, exploratory analysis, and selection of statistical approaches appropriate to the study design.
Data visualization
PCA, heatmaps, group-comparison plots, clustering displays, and other visual approaches used to evaluate study structure and communicate metabolomics results.
Feature annotation
Accurate-mass and MS/MS-based annotation, isotope and adduct information, database and libarary searching, annotation confidence, and the distinction between a molecular feature and a confirmed compound identity.
Targeted & untargeted metabolomics
How targeted quantitative assays and untargeted discovery workflows differ in experimental goals, acquisition strategies, data processing, and interpretation.
Hands-on laboratory training
Practical experience at the bench
Participants gain direct experience with sample handling and preparation techniques used in metabolomics workflows, with instructor guidance throughout the laboratory session.
Instrumentation
Hands-on training on high-resolution and quantitative platforms
Instrument training is performed using Thermo Scientific mass spectrometry platforms used routinely in the Core for untargeted discovery and targeted quantitative analysis.
Thermo Scientific Orbitrap systems
Training on high-resolution accurate-mass LC-MS workflows, including untargeted small-molecule analysis, data acquisition concepts, MS/MS, and feature annotation.
Triple-quadrupole LC-MS/MS systems
Training on targeted quantitative workflows, including method setup, calibration, internal standards, quantitative performance, and interpretation of targeted assay data.
Workflow
Data analysis workflows for interpretation of metabolomics data
Students gain experience with data processing for both targeted quantitation and untargeted discovery workflows.
Interested in metabolomics training?
Training is designed to benefit participants with different levels of experience and can emphasize the parts of the metabolomics workflow most relevant to their research goals.