Lipidomics provide unprecedented phenotypic details by accumulating large amounts of data. While these are potentially of great value, the amount and complexity of the data can be intimidating initially.
This webinar is designed to show the basics of lipidomics analysis. It will cover the characteristics of the datasets, e.g. their lipid substructure and multicollinearity, and how to deal with them. We will go through data preparation, how to calculate new features and how to use principal component analysis as a first impression. Then we will focus on univariate and correlation analysis combined with enrichment analysis.
Here is what you can learn
• General properties of lipidomics datasets • Data cleaning and generation of new features • How to perform univariate analysis • What is enrichment analysis and how is it applied
After receiving his PhD on lipidomics, Dr. Mathias Gerl investigated protein-lipid interactions. In his role as Head of Data Science, Mathias is passionate about finding meaning in large datasets.
