Metabolomics_lectures

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Metabolomics Lectures

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

Day One

• Our R cheatsheet - Rmd
  • Practical: tidyverse & purrr hands on
• What is Metabolomics
• Experimental design
  • Practical: html - Rmd
• 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

Day Two

• Practical: Wrangling a targeted metabolomics data matrix - Rmd

Focus Topics

• Missing values and imputation
• Distribution of the variables
• Variable scaling and Sample normalization
• Multivariate visualization: PCA

Datasets

• KOMP data
• Rubus data

Day Three

• 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

Datasets

• Wines Dataset

Day Four

• Biomarker discovery: the univariate way
• False discoveries, and multiple testing
• Machine Learning for Dummies
  • KOMP data
• PLS and PLS-DA
• Decision Trees and Random Forest
  • Practical: html, Rmd