Welcome to the GitHub repository for the Hands-on Data Analysis for Metabolic Profiling course provided by Imperial International Phenome Training Centre (IIPTC). Here you will finds links to the tutorials as well as local tutorial files and Jupyter notebooks in their respective repositories.

While this course does not involve writing any code, the tutorials are set in Python and a basic knowledge of Python or another programming language is recommended. Prior to taking this course, we encourage working through the first three episodes (Python Fundamentals, Analysing Patient Data, Visualising Tabular Data) from Programming with Python, a free course by Software Carpentry.

For tutorials on Google Colab, please save a copy of the notebook into your Google Drive account so you can edit and save your changes.

• NMR pre-processing
• LC-MS pre-processing

• Data Scaling and Normalisation: (LC-MS, NMR)
• Multivariate Analysis: PCA: (LC-MS, NMR)
• Univariate analysis: (LC-MS, NMR)

• Multivariate Analysis: PLS-DA: (LC-MS, NMR)

• Pathway analysis tutorial

• Caroline Sands (caroline.sands@imperial.ac.uk)
• Humma Hussain (h.hussain@imperial.ac.uk)
• Lukas Kopecky (l.kopecky22@imperial.ac.uk)
• Cecilia Wieder (cw2019@ic.ac.uk)
• Thomas Rix (tom.rix21@imperial.ac.uk)