As part of the TARGETWISE project, LIOS hosted the advanced training course “R Programming for Statistics and Machine Learning”, delivered by Dr. Nikolay Oskolkov (Metabolic Research Group Leader, LIOS, Riga, Latvia) and Dr. Daniel Rivas (Postdoctoral Fellow, Metabolic Research Group, LIOS, Riga, Latvia).

The course was designed for participants with beginner to basic R experience who aimed to advance their programming and computational data-analysis skills. Emphasis was placed on developing a deeper understanding of statistical and machine-learning methods by implementing key algorithms from scratch in base R, alongside strengthening knowledge of data structures, programming paradigms, and functional programming. Practical examples and applications were explored in the context of bioinformatics.

Key topics covered

• Non-parametric and permutation-based statistical tests
• Linear Mixed Models (LMMs)
• Dimensionality reduction methods: PCA, t-SNE, UMAP
• Clustering algorithms (e.g., k-means)
• Random Forests
• Simple neural networks
• Functional programming and advanced data structures in R

Overall, the training strengthened participants’ understanding of statistical modeling and machine-learning principles, with a strong focus on real-world analytical workflows in bioinformatics.