This repository contains material for a full metabolomics course ideally organized in four days. The material (which is growing!) covers the following topics:
- General Introduction to metabolomics and study design
- General analytical considerations
- Analysis of a targeted metabolomics data matrix
- Pre processing of Untargeted LC-MS data by
xcms - NMR
- Introduction to machine learning and multivariate tools
- Statistical analysis of metabolomics data by univariate tools
- Our R cheatsheet - Rmd
- Practical:
tidyverse&purrrhands on
- Practical:
- What is Metabolomics
- Experimental design
- Practical Considerations on the study design
- Group Activity: design your study
- Data analysis in metabolomics
- Practical: Fat data matrices and false positives - Rmd
- Statistical testing and effect size
- Practical: Wrangling a targeted metabolomics data matrix - Rmd
- Missing values and imputation
- Distribution of the variables
- Variable scaling and Sample normalization
- Multivariate visualization: PCA
- Processing LC-MS data with
xcms - Practical: Inspecting raw data html, Rmd
- Practical: Peak picking html, Rmd
- Practical: Retention time correction and feature definition html, Rmd
- SW resources for preprocessing
- Some words on annotation
- Practical: Fragmentation Spectra html, Rmd
- Practical: Compound Annotation html, Rmd
- Wines Dataset
- Biomarker discovery: the univariate way
- False discoveries, and multiple testing
- Machine Learning for Dummies
- PLS and PLS-DA
- Decision Trees and Random Forest
