Introduction to Generalised Linear Models (GLME01) Whether you're working with genotype-phenotype associations, mutation counts, or presence/absence of genetic traits, Generalised Linear Models (GLMs) provide a robust, flexible framework for analysing complex genetic data. This course introduces GLMs from the ground up, with a strong focus on practical application using R—perfect for geneticists aiming to strengthen their statistical toolkit. Who should attend?
- Geneticists and molecular biologists analysing binary, categorical, or count-based genetic outcomes - Researchers working on gene expression, SNP data, mutation load, or inheritance modelling - Bioinformaticians and computational biologists seeking to apply GLMs within their R workflows What you'll learn - Core GLM theory and practical implementation in R, including logistic regression for binary outcomes and Poisson/negative binomial models for count data - Techniques for handling overdispersion and zero-inflated datasets—common in genetic and genomic analyses - How to interpret model outputs, assess fit, and apply GLMs to your own research questions using real biological data Course format - Live online sessions over 10 days, 4 hours a day, combining lectures and hands-on coding in R - Recordings available for all sessions—accessible across time zones - Next session: September 8-12 & 15-19, 2025 - Course fee: First 10 places £400 - Normal price £450 Prerequisites - Basic familiarity with R and RStudio (e.g., importing data, using data frames, and generating basic plots) - A general understanding of statistical concepts such as mean, variance, correlation, and linear regression - No prior experience with GLMs needed—all methods will be introduced from first principles, with an emphasis on interpretation and real-world application ------------------------------ Bring statistical rigour to your genetic research with GLMs Learn to model genetic data confidently and effectively using one of the most versatile frameworks in applied statistics. *Register now or learn more!* For questions or group bookings, contact: *[email protected]* -- Oliver Hooker PhD. PR stats [[alternative HTML version deleted]] _______________________________________________ R-sig-phylo mailing list - [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://www.mail-archive.com/[email protected]/
